Software-Engineer, AI-Engineer, Machine-Learning-Engineer Jobs

Overview

Instacart is transforming the grocery industry by building technology that helps people access the food they love while enabling retailers, brands, and shoppers to thrive. The Enterprise AI team develops intelligent systems and capabilities that support Instacart’s business and teams across the company.

We are seeking a Senior Software Engineer to join the Enterprise AI team and help build reliable, scalable AI-powered solutions. You will work with engineers, product partners, data scientists, and stakeholders across the organization to turn complex business needs into high-quality products and platforms.

This is an opportunity to work on technically challenging problems with broad company impact. You will be expected to take ownership, collaborate across disciplines, and deliver thoughtful solutions in a fast-paced environment where priorities evolve as we learn. The Enterprise AI team is a collaborative group of approximately 14 people, and your work will contribute to the continued growth of Instacart’s AI capabilities.

About the Job

• Design, develop, test, and operate scalable software systems that power Enterprise AI products and capabilities.
• Translate ambiguous business and technical problems into clear engineering solutions, making thoughtful tradeoffs across quality, speed, reliability, and long-term maintainability.
• Collaborate with product managers, data scientists, machine learning engineers, and partner teams to deliver AI-enabled experiences that address meaningful business needs.
• Own projects through the full software development lifecycle, from technical design and implementation through launch, monitoring, and continuous improvement.
• Contribute to engineering excellence through code reviews, design discussions, automated testing, observability, documentation, and operational best practices.
• Help shape the technical direction of the Enterprise AI team by identifying opportunities, evaluating new approaches, and sharing knowledge with teammates and cross-functional partners.

You will be working in a dynamic environment where requirements may change and the most valuable path forward is not always obvious. Success in this role requires comfort with ambiguity, a willingness to investigate problems deeply, and the judgment to make progress while maintaining a high bar for quality and reliability.

About You

Minimum Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• At least five years of professional software engineering experience building and operating production systems.
• Proficiency in at least one modern programming language, such as Python, Java, Go, or C++.
• Experience designing, implementing, testing, and troubleshooting distributed or highly scalable software systems.
• Experience collaborating with cross-functional partners to define requirements and deliver software from concept through production.
• Demonstrated ability to communicate technical decisions clearly, participate in constructive code and design reviews, and take ownership of complex projects.

Preferred Qualifications

• Experience building AI- or machine learning-enabled products, platforms, or developer tools.
• Experience with large language models, retrieval-augmented generation, intelligent automation, model serving, or related Enterprise AI technologies.
• Experience with cloud infrastructure, data platforms, APIs, distributed systems, and production observability.
• Experience improving the reliability, performance, security, or cost efficiency of software systems at scale.
• Ability to lead technical projects, mentor engineers, and influence decisions across organizational boundaries.
• Experience working effectively in a fast-changing environment where priorities, requirements, and technical approaches evolve over time.

Originally posted on Himalayas

Job Summary

Own the agentic systems at the center of Orbis AI — the orchestration, planning, retrieval, and tool-use machinery behind the Agent Catalog and the OSINT Agent Harness. You will build agents that hold up under real mission workloads and set the evaluation bar the rest of the organization writes against. This is senior engineering on AI systems: the hard problems are correctness, explainability, cost, and behavior at scale.

Travel: Up to 15% for customer engagement, integration support, and team collaboration.

Key Responsibilities

• Architect and ship agents across the portfolio — knowledge agents over customer data, tool agents that wrap external operations, and goal-driven agents that plan and execute multi-step analysis.
• Own the orchestration layer: planning, tool selection, state and memory, retries, partial failure, and termination behavior.
• Design and own retrieval end to end — chunking, embedding, indexing, ranking, and the query-time behavior that decides answer quality.
• Build the provenance and citation paths that let a user see how a conclusion was reached, and treat unexplainable output as a defect rather than a limitation.
• Own the evaluation infrastructure for agent quality — accuracy, groundedness, explainability, latency, and cost — and set the standard other engineers write cases against.
• Integrate model providers and third-party tools behind stable internal interfaces, and instrument agents so quality regressions and cost anomalies surface before a customer finds them.
• Partner with research engineers to productionize validated results, and mentor engineers moving into AI work from a conventional software background.
• Travel up to 15% for customer engagement, integration support, and team collaboration.

Required Qualifications

• 4+ years of professional software engineering experience, including 2+ years building LLM-backed or agentic systems in production
• Bachelor's degree in Computer Science, a related technical field, or equivalent professional experience
• Strong programming skills in Python and/or TypeScript, with substantial production code in at least one
• Deep practical experience with retrieval-augmented generation — embeddings, vector search, chunking strategy, ranking, and the failure modes of each
• Demonstrated experience building and debugging multi-step, tool-using agents, whether on a framework or from primitives
• Proven rigor about evaluation, including harnesses that measured whether an AI change actually improved anything
• Willingness to travel up to 15%

Desired Qualifications

• Experience with knowledge graphs, ontologies, entity resolution, or information extraction
• Experience running open-weight models in constrained or disconnected environments where a hosted API is not an option
• Experience with production observability and cost control for model-backed workloads
• Familiarity with OSINT, intelligence, or research workflows and the accuracy and provenance expectations that come with them
• Experience mentoring engineers into AI work from a conventional software background
• Open-source contributions, publications, or academic collaboration in applied AI

Physical Requirements

• Prolonged periods of sitting at a desk and working on a computer
• Participation in virtual and in-person meetings
• Ability to attend planned meetings and/or work in classified spaces for extended periods within the specified work regions
• Travel: Up to 15% for customer engagement, integration support, and team collaboration.

Originally posted on Himalayas

Company Overview

At Motorola Solutions, we believe that everything starts with our people. We’re a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. We build and connect technologies to help protect people, property and places. Our solutions foster the collaboration that’s critical for safer communities, safer schools, safer hospitals, safer businesses, and ultimately, safer nations. Connect with a career that matters, and help us build a safer future.

Department Overview

Job Description

As a Software Engineer in our Command Center Solutions Services engineering group, you will play a crucial role in designing, developing, and optimizing enablement applications for our deployment engineering resources leveraging AI Models and algorithms. This position requires understanding of modern development languages, strong software engineering principles, and experience with large language models.

Responsibilities:

• Design, develop, and test high-performance modern code for implementing AI models.
• Translate AI/ML models into efficient implementations.
• Develop and maintain unit and integration tests.
• Participate in code reviews and contribute to best practices and documentation.
• Stay up-to-date with the latest advancements in AI and LLM systems.

Qualifications:

• Bachelor's degree in Computer Science, Software Engineering, or a related field. Masters is a plus.
• 2-5 years of experience in software development, with a strong emphasis on performance optimization.
• Experience implementing and deploying AI models is highly desired.
• Experience with standards compliance (security or data governance) and requirements traceability is highly desired.
• Proficiency in Python and or Javascript for scripting and tooling.
• Strong understanding of software engineering principles, including design patterns, testing methodologies, and version control (e.g., Git).
• Experience with Linux/embedded Linux development environments.
• Excellent problem-solving and debugging skills.
• Ability to work independently and as part of a team.
• Strong communication and collaboration skills.
• Experience with CI/CD systems like GitHub Actions or Azure DevOps is also a plus.
• Experience with dataflow automation tools such as n8n is also a plus.

Target Base Salary Range: $95,000 - $105,000 USD

Consistent with Motorola Solutions values and applicable law, we provide the following information to promote pay transparency and equity. Pay within this range varies and depends on job-related knowledge, skills, and experience. The actual offer will be based on the individual candidate.

Basic Requirements

Required Skills:

• High School diploma, Bachelor's degree plus 2-5 years of Software development experience as required for this position.
• Legal authorization to work in the U.S. indefinitely is required. Employer work permit sponsorship is not available for this position.

Travel Requirements

Relocation Provided

Position Type

Referral Payment Plan

Our U.S. Benefits include:

• Incentive Bonus Plans

• Medical, Dental, Vision benefits

• 401K with Company Match

• 10 Paid Holidays

• Generous Paid Time Off Packages

• Employee Stock Purchase Plan

• Paid Parental & Family Leave

• and more!

EEO Statement

Motorola Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion or belief, sex, sexual orientation, gender identity, national origin, disability, veteran status or any other legally-protected characteristic.

We are proud of our people-first and community-focused culture, empowering every Motorolan to be their most authentic self and to do their best work to deliver on the promise of a safer world. If you’d like to join our team but feel that you don’t quite meet all of the preferred skills, we’d still love to hear why you think you’d be a great addition to our team.

We’re committed to providing an inclusive and accessible recruiting experience for candidates with disabilities, or other physical or mental health conditions. To request an accommodation, please complete this Reasonable Accommodations Form so we can assist you.

Originally posted on Himalayas

WHO WE ARE

WHAT YOU BRING TO THE TABLE

• Minimum of 8 years of professional software engineering experience, including recent experience shipping production LLM-powered applications or agent systems.

• A track record of technical leadership, including owning the technical direction of a team or major system and influencing architecture beyond your immediate area of ownership.

• Expert-level proficiency in Python, with a history of architecting production APIs and backend services and integrating with protocols such as MCP and A2A.

• Deep experience building and operating production-grade agentic systems with frameworks such as Strands, LangChain, or the Claude Agent SDK, including asynchronous and event-driven patterns, prompt engineering, structured outputs, and techniques for improving agent reliability. Sound judgment on when to optimize for speed and when to invest in quality.

• Experience with evaluation and observability tools such as Langfuse or LangSmith, including designing evaluation strategies from the ground up.

• Fluency with AI coding tools (Claude Code, Cursor, Codex, etc.) as a core part of the development workflow, paired with strong judgment and full ownership of AI-generated output.

• Proven ability to mentor engineers and to explain complex agentic systems clearly to engineers, Product and Operations partners, and non-technical stakeholders.

• Thoughtful approach to collaboration, design, and decision-making that prioritizes equity, access, and continuous learning, and a commitment to creating inclusive, respectful environments where all voices are valued and supported.

BONUS POINTS

• Bachelor’s or advanced degree in Computer Science, Engineering, or a related field

• Prior experience in ad tech, media planning systems, or programmatic advertising platforms.

• Hands-on experience with AWS Bedrock, including Bedrock AgentCore (Runtime, Gateway, Identity).

• Experience designing MCP tool sets or skills libraries adopted by multiple teams or external partners.

• Experience with authentication and authorization for non-human actors, such as OAuth 2.0 flows for agents and token vaulting for third-party integrations.

• Experience with RAG systems, vector databases, or knowledge retrieval approaches.

OUR TECH STACK

• Languages: Python

• Frameworks: LangChain, LangGraph, FastMCP, FastAPI

• Protocols & Integrations: MCP, A2A, AG-UI, REST APIs

• Evaluation & Observability: Langfuse, custom evaluation frameworks

• Data: Snowflake, S3

• Infrastructure: AWS, AWS Bedrock (including Bedrock AgentCore)

Integrity in Hiring

Anything Else?

Life With Basis

Originally posted on Himalayas

Worth AI, a leader in AI onboarding and underwriting, is looking for a talented and experienced Senior Software Engineer - AI Innovation to join our team. At Worth AI, we are on a mission to revolutionize decision-making with the power of artificial intelligence helping fintechs, lenders, payment processors, and financial institutions onboard small businesses faster, smarter, and more confidently. We’re building the infrastructure that powers real-time KYB, KYC/IDV, underwriting, and continuous risk monitoring at enterprise scale, and the Worth Score™ our unified credit score derived from 1,200+ data points across 700M+ SMBs.

As a Senior Software Engineer - AI Innovation, you won’t be wiring up demos you’ll be designing and shipping production agent systems that make consequential decisions on regulated financial data. Worth’s platform consolidates onboarding and underwriting into a single AI-powered system, and our agents read, reason over, and act on the messy, high-stakes signals that come with that domain. You’ll own the end-to-end lifecycle: architecting agent graphs, building the retrieval and tool layers they rely on, instrumenting them with evals and observability, and getting them deployed against SOC 2 / GDPR / CCPA guardrails. You’ll partner closely with our Chief AI Officer, applied scientists, product, and platform teams to turn agentic patterns into customer outcomes.

Responsibilities

• Design and ship multi-step agentic systems (planner/executor, tool-using, multi-agent, human-in-the-loop) that automate KYB, underwriting, case review, and risk monitoring workflows.
• Architect agent graphs in LangGraph (or comparable frameworks CrewAI, AutoGen, Claude Agent SDK) with explicit state, durable execution, retries, and safe fallbacks.
• Build and harden the retrieval layer powering our agents chunking strategies, hybrid search, reranking, and grounded citation across SoS filings, IRS records, bank data, and Worth’s 700M+ SMB graph.
• Own the eval stack: golden sets, offline regression suites, LLM-as-judge, online A/B and shadow evals, and red-teaming for jailbreaks, prompt injection, and PII leakage.
• Wire agents into Worth’s production systems via well-typed tools, MCP servers, and existing services (decisioning engine, case management, crosswalking). Treat tool surface area as a product.
• Drive production MLOps for agents: deployment, versioning, traffic shaping, cost/latency budgets, observability (traces, token spend, tool call success), and on-call playbooks for agent incidents.
• Partner with security, compliance, and legal to keep agents inside Worth’s SOC 2, GDPR, CCPA, and fair-lending posture — building from day one, not bolted on.
• Translate ambiguous product bets (“what if the underwriter had an AI co-pilot for this?”) into concrete agent designs, prototypes, and shipped features.
• Mentor engineers across the org on agent patterns, prompt engineering hygiene, eval discipline, and the failure modes of LLM systems.
• Stay ahead of the frontier new models, frameworks, and patterns — and bring back what actually works in production.

Technology Stack

• Languages & Runtimes: Python, Node.js, TypeScript
• Agent / LLM frameworks: LangGraph, LangChain, Claude Agent SDK, MCP, OpenAI SDK
• Models: Anthropic Claude, OpenAI, open-weight (Llama, Mistral) where appropriate
• Retrieval & Data: PostgreSQL, pgvector / vector DBs, OpenSearch, Kafka, Redshift, Redis
• Infra & Orchestration: AWS, Kubernetes (EKS), ArgoCD, Terraform
• Evals & Observability: LangSmith / Langfuse / Braintrust-style tooling, DataDog, custom eval harnesses

Requirements

• 8+ years of professional software engineering experience, with at least 2 years building production LLM or agentic systems (not just notebooks or demos).
• Solid software engineering experience - front-end, APIs, async patterns, queues, databases, and the failure modes of distributed systems.
• Demonstrated ownership of major features or subsystems in production.
• Demonstrated experience mentoring junior engineers and raising team quality standards.
• Demonstrated experience with event-driven systems: enrichment, retries, dead-lettering, backpressure.
• Experience managing containerized applications in Kubernetes, EKS, ArgoCD, operators, Kustomize.
• Deep, hands-on experience with at least one modern agent framework (LangGraph strongly preferred) and a track record of shipping agents that actually run, fail gracefully, and recover.
• Real experience with evals you’ve built golden sets, run offline and online evaluations, and used them to make ship/no-ship calls.
• Production MLOps fluency: you’ve deployed LLM workloads under real latency, cost, and reliability constraints, and you instrument what you ship.
• Strong proficiency in Python; comfortable in TypeScript / Node.js for integrating with Worth’s services.
• Clear, calibrated communicator - able to explain agent trade-offs to product, security, and customers without hand-waving.
• Operates with extreme ownership in ambiguous, fast-moving environments. Excited to work alongside a team that values “One Team”, “Extreme Ownership”, and “Create Raving Fans.”

Success Metrics

• Agent Quality: Measurable improvements in task success rate, grounding accuracy, and hallucination rate on Worth’s eval suites, tied to customer-visible outcomes.
• Production Reliability: Agents you own meet defined SLOs for latency (P90/P99), tool-call success rate, and cost per task.
• Velocity: New agent capabilities go from prototype to production in weeks, not quarters, without skipping evals or guardrails.
• Risk Posture: Zero material incidents tied to prompt injection, PII leakage, or unsafe tool use on agents you own.
• Force Multiplier: Patterns, tools, and eval scaffolding you build are adopted by other engineers across Worth.

Bonus Points (nice to haves, not requirements)

• Prior experience in fintech, lending, payments, KYB/KYC, fraud, or AML — or any other regulated, high-stakes data domain.
• Experience building MCP servers or other structured tool interfaces for LLMs.
• Background in classical ML (ranking, scoring, calibration) you can bring to bear alongside LLM systems.
• Experience designing explainable / auditable AI workflows for regulated environments (SOC 2, model risk management, fair lending).
• Open-source contributions to agent frameworks, eval tooling, or retrieval libraries.
• Hands-on AWS depth (EKS, MSK, RDS, S3, Lambda) and IaC with Terraform.

**All Remote Hires — will be required to travel to Orlando, Florida at least twice per year for Town Halls and team collaboration, in addition to orientation in Orlando, Florida.

Benefits

• Health Care Plan (Medical, Dental & Vision)
• Retirement Plan (401k, IRA)
• Life Insurance
• Flexible Paid Time Off
• 9 paid Holidays
• Family Leave
• Remote
• Hybrid work (for Orlando Associates)
• Free Food & Snacks (Orlando)
• Wellness Resources

Originally posted on Himalayas

Lead Software Engineer, AI Experience Penn Foster Group | Fully remote within the United States

Position Summary As a Lead Software Engineer, AI Experience at Penn Foster Group, you will provide technical leadership for the design and delivery of AI-native products that help millions of learners discover, enroll in, and progress through our programs. You will operate across product, engineering, and platform boundaries—turning ambiguous opportunities into reliable, scalable systems and establishing the technical direction for AI experiences across the organization. This is a hands-on role requiring strong full-stack execution, architectural judgment, and the ability to influence through technical strategy, design, and mentorship. You will help define how Penn Foster builds with AI by developing retrieval pipelines, agentic workflows, evaluation systems, and production-grade model integrations. You will partner with engineering leaders and product teams to identify high-leverage opportunities, shape technical roadmaps, raise engineering standards, and guide initiatives from early exploration through production adoption.

Essential Job Functions

• Define technical strategy and architecture for AI-powered product experiences across the learner and content-authoring ecosystem.
• Design, build, and ship full-stack systems using TypeScript, Vue.js, Node.js, PostgreSQL, and Azure.
• Lead complex, cross-functional initiatives from problem definition through delivery, adoption, and ongoing improvement.
• Establish reusable patterns for retrieval-augmented generation, agentic workflows, model orchestration, prompt management, and human-in-the-loop experiences.
• Design and maintain evaluation frameworks, quality metrics, observability, and feedback loops for LLM-powered features.
• Integrate model APIs from Anthropic, OpenAI, and other providers with careful attention to reliability, latency, token usage, cost, privacy, security, prompt-injection risk, and graceful degradation.
• Own technical direction for AI-powered content authoring and management capabilities.
• Partner with product, platform, design, data, and sibling engineering teams to translate ambiguous problems into coherent technical plans and shippable systems.
• Identify architectural risks, clarify tradeoffs, and make decisions that balance speed, quality, maintainability, and long-term leverage.
• Raise the engineering bar through design reviews, code reviews, technical documentation, operational standards, and effective development practices.
• Mentor and develop engineers across teams, particularly in AI-assisted development, context engineering, evaluation design, system reliability, and agentic workflows.
• Use agentic coding tools such as Claude Code, Cursor, or equivalent to accelerate planning, implementation, testing, and review while maintaining strong standards for correctness, security, and maintainability.
• Ensure that systems are scalable, observable, secure, accessible, and economically sustainable in production.
• Contribute to engineering-wide discussions about responsible AI adoption, technical standards, platform capabilities, and organizational priorities.

Knowledge, Skills, and Abilities

• 10+ years of experience building and operating customer-facing software products.
• Demonstrated impact as a technical leader, staff engineer, principal engineer, tech lead, or equivalent role.
• Strong full-stack engineering fundamentals, including browser technologies, TypeScript, Node.js, PostgreSQL, cloud infrastructure, and distributed systems.
• Experience designing and delivering AI-powered products using LLMs, retrieval systems, evaluation frameworks, agentic workflows, or related technologies.
• A track record of leading complex initiatives that span multiple teams, systems, or organizational boundaries.
• Ability to set technical direction without relying on formal authority and to build alignment among engineers, product leaders, designers, and other stakeholders.
• Strong architectural judgment and the ability to communicate complex tradeoffs clearly to both technical and non-technical audiences.
• Experience creating durable engineering patterns, platforms, or capabilities that enable other teams to move faster.
• Product sensibility and a strong focus on user experience, quality, speed, and measurable outcomes.
• Comfort working in ambiguous environments where the problem, solution, and path to execution must be shaped collaboratively.
• High ownership mentality, with the ability to move between strategy, architecture, implementation, and operational follow-through.
• Experience mentoring engineers and strengthening engineering practices across a team or organization.
• Commitment to building reliable, secure, observable, and cost-effective AI systems.
• Thrives in a remote, async-first environment with a lean, high-output team.
• Experience working at a startup or organization with a high engineering bar and a bias toward meaningful, measurable impact.

Working Conditions & Hiring Process

• U.S. Work Location Requirement: All employees must reside in and perform work within the United States. We do not support international remote work arrangements for this role.
• Travel Expectations: While this is a remote position, occasional travel may be required for team meetings, company events, conferences, summits, and similar activities. Candidates must be willing and able to travel as needed.
• On-Camera Work Environment: We operate in a highly collaborative, remote, on-camera culture. Employees are expected to be on camera during meetings unless extenuating circumstances apply.
• Recorded Video Interviews: All video interviews conducted during the hiring process will be recorded to support internal hiring consistency and process improvement.
• Background Checks: Employment with Penn Foster Group is contingent upon successfully completing applicable pre-employment screening requirements, which may include verification of employment history, education, and criminal background, where permitted by law.
• Identity Verification (Form I-9): As part of our onboarding process, all hires must complete employment eligibility verification in compliance with federal law. This includes remote Form I-9 verification, which may require an in-person identity verification step with an authorized representative.

About Us At Penn Foster Group, we are transforming online learning to help learners by uniting Penn Foster, CareerStep, Ashworth College, James Madison High School, the New York Institute of Photography, the New York Institute of Art and Design, and other education platforms. Together, we create an accelerated path to greater economic mobility through real-world skills and knowledge that enable learners to achieve long-term success. Our history dates back to 1890, when our founder, Thomas Foster, pioneered distance education by offering training by mail for coal miners to gain the skills needed for safer jobs. Today, with the partners who use our education and training programs, we continue that mission by providing accessible training and education for in-demand skills and building a workforce prepared for the future job market.

Equal Employment Opportunity We strive toward Diversity, Equity, and Inclusion at Penn Foster Group by intentionally building teams that are diverse in identities, lived experiences, and ideas, creating a culture where people feel connected to each other and have a sense of belonging. We value diversity, equity, and inclusion because they enable us to maximize the number of learners who reach their goals, deliver the experiences we want them to have, and become the kind of company we want to work in.

What We Offer We offer a robust benefits package that includes medical, dental, vision, flexible spending, generous paid time off, sponsored volunteer opportunities, a 401(k) with a company match, and free access to all of our online programs.

Originally posted on Himalayas