Software-Engineer, Backend-Engineer, AI-Engineer Jobs

Senior Software Engineer — Agentic AI Platform

Location: Remote | Full-time | Competitive Compensation

Apiphani is building the future of intelligent infrastructure automation through agentic AI. We’re looking for a Senior Backend Engineer to help design and build the systems that power Luumen — an AI-driven automation platform used by enterprise IT and managed service providers around the world.

This is a high-impact, zero-to-one engineering role focused on building the backend foundations for large-scale AI orchestration. You’ll work on distributed systems that combine traditional infrastructure automation with large language models (LLMs), retrieval-augmented generation (RAG), and intelligent agents.

What You’ll Do

• Design and implement backend services that enable intelligent agent workflows and autonomous infrastructure actions

• Develop APIs and orchestration layers in Python and TypeScript, integrating LLMs, vector databases, and observability pipelines

• Build scalable systems to support LLM-based reasoning, retrieval, and decision-making across cloud infrastructure

• Integrate with AWS Bedrock and other LLM platforms to support multi-model capabilities

• Develop data access and semantic search layers using vector databases (e.g., pgvector, Pinecone, Qdrant)

• Build robust monitoring, testing, and CI/CD systems to ensure reliability and reproducibility of AI workflows

• Collaborate closely with the product and DevOps teams to design architecture diagrams, plan deployments, and monitor system health

• Write clean, maintainable code with clear documentation and strong adherence to security and performance best practices

• Participate in code reviews, design discussions, and iterative delivery cycles to improve product velocity and quality

What We’re Looking For

• 6+ years of backend engineering experience in production environments

• Strong proficiency in Python and TypeScript for building distributed, event-driven systems

• Deep understanding of AWS services (Lambda, ECS, Bedrock, S3, CloudWatch, etc.)

• Experience designing APIs, microservices, and event pipelines that interface with LLMs or AI models

• Familiarity with vector databases and concepts like embeddings, similarity search, and retrieval-augmented generation

• Experience with infrastructure-as-code tools such as Terraform or AWS CDK

• Understanding of SQL and schema migration workflows (PostgreSQL or similar)

• Hands-on experience with Docker, GitHub Actions, and cloud-native CI/CD workflows

• Ability to diagram systems, communicate architecture decisions clearly, and work asynchronously in a distributed team

• Strong sense of ownership and ability to deliver in fast-moving, ambiguous environments

Bonus Points

• Experience working with LangChain, OpenAI, or Anthropic APIs

• Familiarity with agentic frameworks or AI orchestration systems

• Background in observability or APM tooling (e.g., Datadog, Dynatrace)

• Prior experience building automation or infrastructure management tools

• Contributions to open-source LLM or MLOps projects

• Interest in shaping how AI is applied to real-world IT operations

Why Join Apiphani

You’ll be joining a globally distributed, high-performing team focused on redefining how enterprises manage infrastructure. Every feature you build will directly impact how engineers interact with intelligent systems in production environments.

This is an opportunity to help architect the foundations of a platform that blends infrastructure automation, AI, and agentic reasoning — where your technical decisions will shape the next generation of enterprise operations.

Originally posted on Himalayas

Senior Software Engineer I – Search and AI Platform

About the Team

Our team is dedicated to unlocking the rich knowledge embedded within Elsevier’s content through our rich data platform; this empowers researchers, clinicians, and innovators worldwide to gain new insights, make informed decisions, and accelerate progress across research, healthcare, and life sciences.

As part of this mission, the AI Platform team is focused on building reusable generative AI capabilities that can be embedded across products and platforms. We create scalable, secure, and production-ready AI services — enabling downstream teams to integrate cutting-edge GenAI features with confidence.

The Role

We are seeking a Senior Software Engineer I with a passion for generative AI and platform architecture. In this role, you will drive architectural decision and set engineering standard and implement robust systems to deliver reusable AI services and components, collaborating closely with cross-functional stakeholders to solve meaningful challenges. You will also contribute to mentor other engineers and help evolve our engineering practices.

Responsibilities

• Leading architectural design and ensure technical consistency.

• Designing, developing, and maintain generative AI services and reusable components using mostly Python and a little bit Java.

• Defining and promote best practices in engineering, including scalability, observability, testing, and CI/CD.

• Contributing to system designs spanning multiple services and modules, aligning with architectural best practices.

• Collaborating with product, platform, and research teams to translate AI prototypes into production-ready capabilities.

• Working within a Kubernetes (EKS) environment to deploy scalable, containerized applications.

• Leading the resolution of complex technical challenges across distributed systems.

• Mentoring less-senior developers on engineering principles, GenAI patterns, and platform development.

• Participating in code reviews, architecture sessions, and cross-team initiatives to ensure quality and maintainability.

• Staying informed of the latest developments in generative AI and advocate for responsible integration into product ecosystems.

What We’re Looking For

• 4-6 years of software engineering experience.

• Proven experience contributing to technical architecture for large-scale platforms or services.

• Solid understanding of software development methodologies and data modeling principles.

• Deep expertise in Python and Java.

• Proficiency in backend development and familiarity with modern AI/LLM tools and frameworks (e.g., LangChain, LangGraph).

• Experience with Kubernetes (EKS) and cloud-native architectures.

• Proven track record building scalable backend systems and APIs.

• Experience mentoring engineers and contributing to architectural decisions.

• Ability to work collaboratively across functions in an Agile or Kanban environment.

Nice to Have

• Experience operationalizing LLMs or building internal AI platforms.

• Familiarity with observability practices (metrics, logging, alerts).

• Exposure to knowledge graphs or semantic search systems.

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Originally posted on Himalayas

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

Job Category

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

Engineering at Qualified

Engineering at Qualified is a high-ownership, high-velocity environment where engineers ship customer-facing product to real enterprises at scale. We're building at the frontier of AI + product: developing agentic software and

embedding AI directly into our platform, using modern toolchains and processes that help engineers move faster while staying focused on high-impact problem solving.

Following our acquisition by Salesforce, we continue to operate with the pace and ownership of a startup, backed by the distribution, resources, and long-term runway of a global enterprise. Engineers have true end-to-end ownership from idea to production: scoping, implementation, testing, deployment, monitoring, and iterative improvement based on real customer feedback.

You'll work alongside a high-talent-density team that cares deeply about craft, performance, reliability, and user experience, and that raises the bar through collaboration, code review, and strong engineering principles. You'll make architecture decisions, solve meaningful system design challenges, and see your work land quickly with customers, without layers of approvals slowing you down.

The Role

As an Engineer on the AI Core team, you'll operate as a technical leader who turns ambiguous, high-stakes AI problems into durable, high-quality systems, while raising the technical bar for the broader team. AI Core builds the retrieval systems and agent infrastructure that power how our AI agents find, trust, and use knowledge, and the developer tooling that lets engineers across the company ship production agents quickly and safely.

You'll lead significant initiatives end to end: faithful answering over a customer's own knowledge, retrieval that combines RAG and hybrid search, content lifecycle controls such as freshness, deduplication and source precedence, transcript processing, and the frameworks, registries, and evaluation tooling that make building a production agent a paved path. You'll partner closely with product, design, and engineering leadership to decide what we build, how we build it, and how we measure whether answers actually got better.

What You'll Do

Lead retrieval initiatives end to end: Design, build, and operate retrieval systems using RAG and hybrid search (lexical plus vector, reranking, filtering) so agents answer from the right content with the right amount of context. Own delivery from scope and design through launch, monitoring, and iteration.

Build developer tooling for production agents: Drive technical design for the frameworks and platform pieces our engineers use to build agents, including multi-agent orchestration, shared primitives for prompts, tools, tracing, and evaluation.

Own answer quality: Diagnose why answers are thin, wrong, or inconsistent by separating retrieval problems from generation problems (prompt, token budget, model choice). Set a quality bar we can test against, and lead the

work to reach it.

Design content and data models: Define how content from documents,

knowledge bases, and call transcripts is ingested, segmented, labeled, and retrieved, including the primitives behind freshness, dedupe, source

precedence, and internal versus external visibility.

Make AI changes safe to ship: Build evaluation, observability, and rollout

practices (offline evals, online monitoring, regression detection) so we can change prompts, models, and retrieval with confidence. Evaluate multiple

solution paths and know when to trust, redirect, or override model and agent output.

Set performance and scaling benchmarks across the platform we own:

Define and track targets for retrieval and indexing, LLM provider usage, and agent orchestration.

Own operational health: Ensure the reliability and performance of the systems your team owns. Participate in on-call, lead incident resolution for your area, and communicate clearly with the team and stakeholders during incidents.

Use agentic development to raise leverage: Use coding agents by default for implementation, testing, refactoring, and documentation while holding a high validation bar. Create reusable workflows, patterns, and tooling that raise the effectiveness of your team beyond your own output.

Partner across functions: Work with product, design, and engineering

leadership to shape roadmap, tradeoffs, and requirements, and to translate strategy into concrete execution plans.

Raise team effectiveness: Mentor engineers, give high-quality code review and technical guidance, and improve standards, tooling, and processes.

Who You Are

Proven experience shipping production AI or backend systems in a high ownership environment, with a recent focus on LLM-powered applications.

Expertise building retrieval systems using RAG and hybrid search, including chunking and indexing strategy, embeddings, vector and lexical search,

reranking, and measuring retrieval quality.

Expertise building developer tooling that lets developers build production agents, which can include frameworks for multi-agent orchestration, an agent and tool registry, and shared infrastructure for tracing and evaluation.

Experience owning platform initiatives from design through adoption,

across systems such as retrieval and indexing, LLM provider integrations, and agent orchestration, including driving adoption and evolving the platform as usage grows.

Demonstrated technical leadership: you lead significant projects, design solutions for non-trivial problems by weighing tradeoffs, and influence architecture and execution beyond your immediate workstream.

Strong track record delivering complex projects with multiple stakeholders, dependencies, or phases.

Strong backend engineering fundamentals and proficiency in languages such as Ruby on Rails, Python, JavaScript, or Go, with SQL and RDBMS experience (PostgreSQL preferred).

Hands-on experience with the AI application lifecycle: experiment setup, dataset curation, offline evaluation, error analysis, deployment, and online evaluation.

Comfortable operating in ambiguity and driving clarity: you can frame problems, propose solutions, and align others.

Strong communicator across functions, able to explain technical ideas to both technical and non-technical audiences and to translate complex concepts into business impact.

Ownership mindset and bias for action. You raise the bar for the team through mentoring, code review, and your own work.

Curious and continuously learning, with an agent-forward approach to how you build software.

Nice to Have

Experience with pgvector or other vector indexes, and with query performance at scale.

Experience with content ingestion from third-party systems (document stores, knowledge bases, CRM knowledge objects) and the lifecycle problems that follow: sync state, dedupe, source conflict.

Experience processing conversation or call transcripts, including handling PII and consent constraints.

Experience designing evaluation suites that score qualities such as thoroughness and faithfulness, not only correctness.

Experience with voice or real-time conversational agents.

Experience with enterprise SaaS (especially B2B marketing or sales tech) or Salesforce/CRM integrations.

Startup experience and rapid shipping.

Why Join Qualified

Foundational impact: Shape how our AI agents retrieve, reason, and answer, and the tooling every engineer here uses to build them.

Lead real initiatives: Own significant projects end to end, with scope and

influence that grow as you deliver. You'll own the platform as it scales, from retrieval to model providers to agent orchestration, and set the performance and reliability bar that grows with the company.

AI as a core product surface: Turn new AI capabilities into dependable

experiences that customers trust, with strong engineering around evaluation, observability, and iteration.

High bar, low bureaucracy: Work with a team that values craft and decisive execution, where strong ideas win and shipping is the default.

Room to grow: Take on larger technical and product scope over time: leading projects, influencing architecture, and leveling up quickly.

If you're excited to build retrieval systems and agent infrastructure at the intersection of AI and enterprise software, we'd love to hear from you.

Unleash Your Potential

When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance andbe your best, and our AI agents accelerate your impact so you cando your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.

Accommodations

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Posting Statement

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

Originally posted on Himalayas

As a Senior Software Engineer focused on Agentic, LLM-powered applications, you will design, develop, and optimize intelligent systems and autonomous agents. You will work across the full stack of agent development - from prompt engineering and LLM integration to observability, orchestration, and cloud-native deployment. This role requires deep technical expertise with Python, modern LLM frameworks, and AWS services, along with hands-on experience building reliable, scalable AI-driven systems.

Responsibilities

• Design, develop, and maintain scalable data and application services supporting AI-driven solutions
• Build and maintain workflow orchestration, integration, and automation capabilities across enterprise platforms
• Develop and optimize backend services, APIs, and microservices using modern cloud-native architectures
• Evaluate and implement emerging technologies to improve system reliability, performance, and developer productivity
• Implement monitoring, observability, and operational tooling to ensure platform health and application performance
• Collaborate with cross-functional teams and participate in Agile ceremonies
• Perform peer reviews and contribute to engineering standards and best practices

• Bachelor’s degree in Computer Science or related field
• 5+ years of professional software engineering experience
• Expertise in Python and relevant libraries
• Strong fundamentals in algorithms, distributed systems, and cloud-native design
• Experience building and consuming REST APIs and event-driven systems
• Strong knowledge of AWS services including Lambda, ECS, S3, DynamoDB, API Gateway
• Excellent communication, collaboration, and problem-solving skills
• Self-directed, ability to multi-task, sharp analytical abilities, excellent communication skills

Desired Qualifications

• Experience with vector databases and embedding pipelines
• Experience with real-time or streaming platforms such as Kinesis or Kafka
• Familiarity with containerization technologies such as Docker
• Experience with reinforcement learning or agentic evaluation frameworks
• Results-oriented, high energy, self-motivated
• Experience with LangGraph or similar agentic frameworks
• Some knowledge of LLM model integration and tuning
• Hands-on experience with observability tools such as LangSmith or LangFuse
• Experience developing MCP Servers

Additional Requirements:

Fully Remote: This position has been designated as fully remote, meaning that the position is expected to contribute from a non-NBCUniversal worksite, most commonly an employee’s residence. This position is eligible for company sponsored benefits, including medical, dental and vision insurance, 401(k), paid leave, tuition reimbursement, and a variety of other discounts and perks. Learn more about the benefits offered by NBCUniversal by visiting the Benefits page of the Careers website. Salary range: $120,000 - $160,000.
We are accepting applications for this position on an ongoing basis.

As part of our selection process, external candidates may be required to attend an in-person interview with an NBCUniversal employee at one of our locations prior to a hiring decision. NBCUniversal's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law.

If you are a qualified individual with a disability or a disabled veteran, you have the right to request a reasonable accommodation if you are unable or limited in your ability to use or access nbcunicareers.com as a result of your disability. You can request reasonable accommodations by emailing .

For LA County and City Residents Only: NBCUniversal will consider for employment qualified applicants with criminal histories, or arrest or conviction records, in a manner consistent with relevant legal requirements, including the City of Los Angeles' Fair Chance Initiative For Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, where applicable.

NBCUniversal is one of the world's leading media and entertainment companies. We create world-class content, which we distribute across our portfolio of film, television, and streaming, and bring to life through our global theme park destinations, consumer products, and experiences. We own and operate leading entertainment and news brands, including NBC, NBC News, NBC Sports, Telemundo, NBC Local Stations, Bravo, and Peacock, our premium ad-supported streaming service. We produce and distribute premier filmed entertainment and programming through our powerhouse film and television studios, including Universal Pictures, DreamWorks Animation, and Focus Features, and the four global television studios under the Universal Studio Group banner, and operate industry-leading theme parks and experiences around the world through Universal Destinations & Experiences, including Universal Orlando Resort, home to Universal Epic Universe, and Universal Studios Hollywood. NBCUniversal is a subsidiary of Comcast Corporation. Visit www.nbcuniversal.com for more information.

Our impact is rooted in improving the communities where our employees, customers, and audiences live and work. We have a rich tradition of giving back and ensuring our employees have the opportunity to serve their communities. We champion an inclusive culture and strive to attract and develop a talented workforce to create and deliver a wide range of content reflecting our world.

Originally posted on Himalayas

Position Overview
We are seeking an experienced Senior Software Engineer to design, build, and operate resilient, scalable, high-performing services for the Product Access platform, which supports the access experience for millions of Autodesk users worldwide.

You will own end-to-end solution design and delivery across the full engineering lifecycle and use spec-driven development and agentic systems to build, operate, and support Product Access in production, including agent-based automation for engineering and operational workflows. This role includes shared production on-call responsibilities as part of end-to-end service ownership.

You will report to the Senior Engineering Manager and collaborate closely with Product Managers, Architects, Domain Leads, and cross-functional stakeholders across Product Access and beyond.

Responsibilities

• Design, develop, and operate resilient, scalable, high-performing cloud-native Java microservices and distributed systems on AWS for the Product Access platform
• Own business features and platform initiatives end to end, from requirement analysis through production support, working with product and engineering partners on design, testing, and operational readiness
• Enhance system resiliency, reliability, scalability, and security; optimize performance, troubleshoot production issues, and implement engineering best practices across development and delivery pipelines
• Lead project delivery by organizing scope, estimating effort, establishing timelines, and driving medium-to-large initiatives independently
• Apply spec-driven development in platform and feature delivery
• Build and extend agentic systems and automation: composable skills, MCP integrations, and knowledge retrieval grounded in runbooks, tickets, and service documentation
• Deliver proactive triage and write-action automation with human-in-the-loop gates where required, progressing toward autonomous design-to-delivery workflows
• Enforce production standards for agentic systems through evaluation, CI quality gates, and end-to-end observability across agents and services
• Provide production support; lead incident response and root cause analysis; participate in a shared on-call rotation for production systems, including support outside standard business hours per team schedule; mentor engineers and uphold sound engineering practices

Minimum Qualifications

• Bachelor's degree or higher in Computer Science, Engineering, or a related field, or equivalent practical experience
• 6+ years of progressive software engineering experience building and operating Java microservices and serverless architectures in production
• Strong Java and Spring Boot skills; solid unit, integration, and system testing; strong debugging in local and integrated environments
• Hands-on experience building or integrating AI-powered systems: agents, LLM-based applications, RAG, or tool-calling workflows
• Experience with spec-driven development (SDD)
• Experience with event-driven streaming (Kinesis, Kafka, or equivalent), containers on AWS (Docker, ECS Fargate), CI/CD (Jenkins, GitHub Actions), and core AWS services (Lambda, DynamoDB, messaging, API gateways, logging, monitoring)
• Strong collaboration and communication skills; effective in small teams with shared end-to-end ownership of design, delivery, and production support

Preferred Qualifications

• Proficiency in Python and FastAPI; experience building MCP servers or equivalent tool-use frameworks for AI agents
• Experience with RAG, proactive or event-driven agents, and applying agentic AI to engineering workflows, operational automation, or DevOps
• Experience designing LLM evaluation frameworks, multi-agent patterns, and human-in-the-loop review gates
• Familiarity with high-volume event pipelines (Kinesis/Kafka streaming, REST publish, SNS/SQS/DLQ patterns), Gradle or Maven, OpenTelemetry, and AI tracing tools (Opik, LangSmith, or equivalent)
• Understanding of policy-based access control (OPA), authentication for AI systems (OAuth, Entra ID), and Responsible AI practices

Technologies we use

• Platform: Java, Spring Boot; Python, FastAPI (agentic); AWS (ECS Fargate, Lambda, DynamoDB, SQS, API Gateway, CloudWatch, OpenSearch); Docker; GitHub; Jenkins / GitHub Actions; Gradle / Maven
• Streaming & events: Kinesis, Kafka, REST publish, SNS/SQS fan-out, DLQ handling, checkpointed consumers, multi-language event SDKs
• Observability & ops: Splunk, Kibana, Dynatrace, OpenTelemetry; Jira, Slack
• Agentic AI: LLM agents, MCP, RAG and vector retrieval, spec-driven development, evaluation and CI quality gates for production AI
• Security & access: OAuth, Entra ID, OPA and policy-based access control

Exposure to equivalent technologies is welcome.

About Autodesk

Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.

We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.

When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!

Benefits

From health and financial benefits to time away and everyday wellness, we give Autodeskers the best, so they can do their best work. Learn more about our benefits in the U.S. by visiting

Equal Employment Opportunity

At Autodesk, we're building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world. Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law.

Belonging

We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here:

In-Person Onboarding and Identity Verification

This role may require in-person onboarding and/or in-person ID verification.

Originally posted on Himalayas

The Role

What You’ll Do

What We’re Looking For

Technology Stack

Strength in the required technologies matters most. Nice-to-have technologies are a plus, not a filter.

Required

• Languages: TypeScript and Python (strong), SQL (solid)

• Backend and APIs: REST APIs in Node.js or Python (e.g., Express, NestJS, FastAPI or Django); background jobs and queues

• Cloud and infrastructure: AWS, GCP or Azure; Docker; CI/CD

• Data engineering: Batch pipelines with Airflow, Dagster or dbt; data quality testing

• Applied AI and LLMs: LLM APIs (OpenAI, Anthropic or similar); prompt design; measuring output quality

• Observability: Logging, metrics and alerting for production services

Nice to Have

• Backend and APIs: Event-driven systems (Kafka, SQS or Pub/Sub)

• Cloud and infrastructure: Kubernetes, Terraform, Pulumi

• Data engineering: Snowflake, BigQuery or Redshift; Metabase

• Applied AI and LLMs: RAG and vector search (pgvector, Pinecone); OCR and document AI (Textract, Google Document AI, Azure Document Intelligence)

• Observability: Sentry, PostHog or Datadog

Originally posted on Himalayas

Who We Are:

At OPENLANE we make wholesale easy so our customers can be more successful.

We’re a technology company building the world’s most advanced—and uncomplicated—digital marketplace for used vehicles.

We’re a data company helping customers buy and sell smarter with clear, actionable insights they can understand and use.

And we’re an innovation company accelerating the future of wholesale remarketing through curiosity, collaboration, and an entrepreneurial spirit.

Our Values:

Driven Waybuilders. We pursue challenges that inspire us to build, create, and innovate.

Relentless Curiosity. We seek to understand and improve our customers’ experience.

Smart Risk-Taking. We transform risk into progress through data, experience, and intuition.

Fearless Ownership. We deliver what we promise and learn along the way.

We’re hiring AI-first Sr. Software Engineers to build, evolve, and scale OPENLANE’s U.S. marketplace platforms.

These roles are for engineers who already treat AI as a first-class development tool, not a novelty. You’ll use AI to move faster, ship higher-quality software, and reduce operational and development toil, while still applying strong engineering judgment, ownership, and systems thinking.

You’ll work on customer-facing marketplace experiences and core platform services, partnering closely with Product, Data, Infrastructure, and SRE teams to deliver resilient, scalable systems.

AI is an accelerator. Engineering ownership still matters.

Why OPENLANE:

• Work on real-time, high-value marketplace systems at scale

• Be part of a major platform modernization and AI transformation

• Use AI as a first-class development tool—not an experiment

• Collaborate with experienced engineers, product leaders, and platform teams

• Grow in an environment that values learning, ownership, and impact

You Are:

• AI-forward. You already use AI tools to enhance development speed, quality, and efficiency, and you continuously adapt as tooling evolves.

• Product-minded. You think beyond code and understand how technical decisions impact customers and business outcomes.

• Ownership-driven. You take responsibility for systems end-to-end, including reliability and operational health.

• Technically curious. You enjoy learning new technologies and thoughtfully evaluating emerging approaches.

• Quality-focused. You value clean, maintainable code, strong testing practices, and production-ready engineering standards.

You Bring:

Core Engineering Skills

• Experience building and supporting production software systems

• Strong understanding of APIs, distributed systems, and cloud-native architecture

• Comfort working in modern CI/CD environments

• Experience with observability, monitoring, and incident response

• Ability to own features and systems end-to-end

AI-First Mindset

• Actively uses AI development tools (code copilots, AI debuggers, test generators)

• Curious about applying AI to real customer and business problems

• Able to critically evaluate AI outputs instead of blindly accepting them

• Comfortable learning and adapting in a fast-changing tool landscape

Technical Experience (One or More)

• Backend development (Java, Kotlin, Go, Python, .NET, Ruby, or similar)

• Frontend experience (React, TypeScript) is a plus

• AWS or similar cloud platforms

• Microservices and event-driven architectures

• SQL and data-driven applications

You Will:

• Design, build, and operate scalable services that power U.S. marketplace workflows such as Buy Now, 45M, Simulcast, and DealerBlock

• Develop APIs and backend services on the modern, cloud-native, AI-enabled platform

• Embed AI-driven capabilities into marketplace features including pricing logic, negotiation flows, and workflow automation

• Use AI tools to accelerate coding, testing, debugging, and documentation while applying strong engineering judgment

• Partner with Product to translate business needs into durable, scalable technical solutions

• Participate in on-call rotations and support live production systems

• Improve system reliability, performance, security, and observability

• Contribute to technical direction, engineering standards, and long-term platform evolution

How You’ll Use AI in These Roles:

• AI-assisted coding and refactoring

• AI-generated test coverage and validation

• AI-supported debugging and root-cause analysis

• AI-assisted documentation and knowledge sharing

• Applying AI tools to reduce repetitive work and increase engineering leverage

Who You Will Work With:

Reporting to an Engineering Manager, this role collaborates closely with Product Managers, Data Engineers, Infrastructure, and Site Reliability Engineering (SRE) teams on a daily basis

Must Have’s:

• 5+ years of experience building and supporting production software systems

• Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)

• Experience building and supporting production software systems

• Backend development (Java, Kotlin, Go, Python, .NET, Ruby, or similar)

• Strong understanding of APIs, distributed systems, and cloud-native architecture

• Comfort working in modern CI/CD environments

• Experience with observability, monitoring, and incident response

• Ability to own features and systems end-to-end

• Actively uses AI development tools (code copilots, AI debuggers, test generators)

• Curious about applying AI to real customer and business problems

• Able to critically evaluate AI outputs instead of blindly accepting them

• Comfortable learning and adapting in a fast-changing tool landscape

Nice to Have’s:

• Frontend experience (React, TypeScript)

• AWS or similar cloud platforms

• Microservices and event-driven architectures

• SQL and data-driven applications

• Marketplace, e-commerce, or high-volume transaction systems

• Reliability engineering or SRE experience

• Experience modernizing or migrating legacy systems

What We Offer:

• Competitive pay

• Medical, dental, and vision benefits with employer HSA contributions (US) and FSA options (US)

• Immediately vested 401K (US) or RRSP (Canada) with company match

• Paid Vacation, Personal, and Sick Time

• Paid maternity and paternity leave (US)

• Employer-paid short-term disability, long-term disability, life insurance, and AD&D (US)

• Robust Employee Assistance Program

• Employer paid Leap into Service Day to volunteer

• Tuition Reimbursement for eligible programs

• Opportunities to expand your skill set and share your knowledge across a publicly traded, global organization

• Company culture of internal promotions, diverse career paths, and meaningful advancement

Sound like a match? Apply Now - We can't wait to hear from you!

Compensation Range of

(Depending on experience, skill set, qualifications, and other relevant factors.)

Originally posted on Himalayas

Job Type: Contractor (~15 hrs a week)

Location: Remote

Schedule: Flexible, you pick the hours and days (including weekends if desired)

Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

You'll create realistic, interesting and challenging coding tasks for AI to solve involving feature implementation and bug fixes, and implement deterministic verifiers that accept reasonable valid solutions and reject everything else.

Required Skills

• Python3

• JAVA

• Rust

• Algorithms

• Basics C++

• Typescript

• bug fixing

• feature implementation

• codebase refactoring

• performance optimization

What we're looking for

• Strong backend experience in Java, Node.js, Go, Rust, Typescript, Python, C++ or similar

• A track record building scalable services and APIs

• Comfort with debugging, performance work and automated testing

• Solid code review instincts

• A strong testing background is a big plus — experience designing test strategy, building and maintaining large test suites, diagnosing flaky tests, or raising the testing bar on a team.

Preferred Qualifications

• Proven experience in backend development, with a track record of delivering high-quality and performant projects.

• Demonstrated success in identifying and resolving software bugs and system bottlenecks.

• Experience with codebase refactoring and implementing complex features in large-scale applications.

• Strong understanding of algorithms, data structures, and foundational computer science concepts.

• Excellent analytical, problem-solving, and technical communication skills.

A note on the process: our interview and assessment stages are designed to see how you think, so we ask that you complete them without outside assistance. The same applies once you're on the project — the value of the work comes from your own judgment.

Process:

• Apply to the role, filling out the screening questions

• Complete AI Interview (approx. 30 minutes)

• Technical Assessment (Tentative)

• Hiring Manager review

Compensation Structure

Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.

Start Timeline & Availability

We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.

Originally posted on Himalayas