Software-Engineer, Distributed-Systems-Engineer, Backend-Engineer Jobs

Software Engineer, Distributed Systems (Core)

Company: Hightouch
Location: Remote (United States or Canada)
Compensation: $180,000 - $320,000 + competitive equity
Employment Type: Full-time
Visa Sponsorship: Visa transfers (can sponsor most visas)

About Hightouch

Hightouch pioneered the Composable Customer Data Platform (CDP), which lets companies use their own data warehouse to collect, prepare and activate customer data for marketing personalization and business operations. Its AI Decisioning platform lets marketers set goals and guardrails that AI agents use to personalize 1:1 customer interactions. Hundreds of companies, including Autotrader, Calendly, Cars.com, Monday.com and PetSmart, rely on it.

Founded in 2018, Hightouch has about 350 people and has raised $320M+ through Series D.

The Role

Hightouch is hiring distributed systems engineers to work on the syncing engine that customers and other engineering teams rely on to move massive amounts of customer data. You will apply expertise in distributed systems, performance optimization and troubleshooting across a multi-cloud, multi-region infrastructure that serves a global customer base. Engineers get very high ownership: you deliver projects start to finish, work directly with customers on their hardest scaling problems and shape what the team works on.

What You Will Do

• Speed up syncs of large data volumes to destinations like Facebook and Snapchat by optimizing every part of the sync process.
• Extend batch syncing into real-time streaming syncs from sources such as webhooks and queues.
• Find and remove scaling and reliability bottlenecks and architect for the next order of magnitude of growth.
• Evolve the Personalization API, a low-latency caching layer over data warehouses serving sub-30ms p90 responses at millions of QPS.
• Extend the multi-region, multi-cloud backend to new regions to meet customer data-residency requirements.

What You Bring

• 7+ years as a software engineer with deep distributed systems work
• Staff-level scope with fast promotion history at high-growth startups (Series A to E)
• Very strong systems design fundamentals and understanding of how large-scale distributed systems behave
• Built event collection or data streaming services that power critical systems (message queues, Kafka, SQL databases, Kubernetes, Docker)
• Owned systems through orders-of-magnitude growth
• A pure backend focus (this is not a full-stack, data engineering or DevOps role)
• Excellent communication and fast learning

Nice to Have

• Built data sync engines moving terabytes per day
• Work close to the infrastructure layer; understands how tools like Spark, Flink and Kafka are built
• Degree from a top computer science program

Interview Process

Recruiter screen (30 min), hiring manager interview (30 min), system design screen (45 min), system design interview (90 min), final call.

Tech Stack

Distributed systems, Kafka, message queues, SQL databases, Kubernetes, Docker, multi-cloud

Originally posted on Himalayas

About Stairwell

Stairwell is building the future of threat detection and malware analysis. Our platform helps security teams find threats that others miss by transforming how organizations collect, analyze, and act on file-based intelligence. We're a small, high-impact team solving hard problems at the intersection of cybersecurity and large-scale data systems.

The Role

We're looking for a senior systems engineer who has personally designed and operated large-scale distributed infrastructure in production. You think from first principles, have real hands-on experience with storage or distributed systems, and naturally reason about tradeoffs and failure modes rather than reaching for the nearest familiar pattern. You enjoy building foundational infrastructure in ambiguous, still-being-defined environments, and you know how to use AI as a productivity tool without letting it substitute for your own engineering judgment.

You'll design and build the infrastructure that powers our threat detection platform — systems that process massive volumes of data with high reliability and performance. Engineers at Stairwell know their customer, know the business, and know the architecture well enough to make sound design decisions independently. We build AI-first, and expect you to reach for tools like Claude Code, Copilot, or similar as your default way of working — while knowing exactly where to trust them and where your own judgment has to lead.

What You'll Do

• Design, build, and operate distributed systems in Go that handle large-scale data ingestion, processing, and analysis

• Work across the stack on storage systems, message queues, APIs, and data pipelines

• Collaborate with security researchers, subject-matter experts, and other engineers to turn threat detection concepts into scalable infrastructure

• Improve system reliability, observability, and performance as we grow

• Contribute to our engineering culture around AI-augmented development - sharing patterns, workflows, and lessons learned

What We're Looking For

• Strong experience building production distributed systems (consensus, replication, fault tolerance, etc.)

• Deep proficiency in Go; you write idiomatic, maintainable code

• Practical experience with AI coding assistants as part of your regular development workflow - not just experimentation, but daily use

• Ability to critically evaluate AI-generated code: you know when to trust it, when to revise it, and when to write it yourself

• Comfort with ambiguity and ownership; we're a small team where engineers drive decisions

• Experience with cloud infrastructure (GCP preferred), containerization, and infrastructure-as-code

Nice to Have

• Background in security, malware analysis, or threat detection

• Experience with large-scale data systems, particularly Google BigTable, Spanner, etc.

• Contributions to open-source distributed systems projects

Why Stairwell

• Hard technical problems with real security impact

• Small team, huge impact, high autonomy, low process overhead

• Opportunity to collaborate with world-class experts in cybersecurity

• Work remotely in the USA or Canada, or use our co-working space in Santa Clara to collaborate with teammates in-person

Originally posted on Himalayas

NVIDIA is hiring experienced software engineers with Kubernetes experience to help scale up its AI Infrastructure. We expect you to have significant software engineering experience with Kubernetes including cluster operations, operator development, node health monitoring and working with GPU resource scheduling. We welcome out-of-the-box thinkers who can provide new ideas with strong execution bias. Expect to be constantly challenged, improving, and evolving for the better. You will help advance NVIDIA's capacity to build and deploy leading infrastructure solutions for a broad range of AI-based applications. If you're creative, passionate about Kubernetes and GPUs, and love having fun, please apply today!

For two decades, we have pioneered visual computing, the art and science of computer graphics. With the invention of the GPU - the engine of modern visual computing - the field has expanded to encompass video games, movie production, product design, medical diagnosis and scientific research. Today, we stand at the beginning of the next era, the AI computing era, ignited by a new computing model, GPU deep learning.

What you will be doing:

• You will be part of an DGX Cloud team responsible for production systems that enable large scalable GPU clusters to be used for a variety of AI workloads. This includes working on custom software related to scheduling GPU resources on Kubernetes.
• Implementing monitoring and health management capabilities that enable industry leading reliability, availability, and scalability of GPU assets. You will be harnessing multiple data streams, ranging from GPU hardware diagnostics to cluster and network telemetry.
• Working with teams across NVIDIA to ensure production AI clusters run reliability and consistently with maximum performance. Evaluating system failures and improving services based on a well-defined incident management process.

What we need to see:

• Direct experience in a software engineering role within a highly technical organization with demonstrable impact from your work. Software development experience with Kubernetes APIs and frameworks not just operating a cluster.
• Highly motivated with strong communication skills, you can work successfully with multi-functional teams, principles, and architects and coordinate effectively across organizational boundaries and geographies.
• 5+ years in similar role and experience on large-scale production systems. Experience with common software engineering principles, tools and techniques.
• You possess a BS in Computer Science, Engineering, Physics, Mathematics or a comparable Degree or equivalent experience.
• Technical knowledge, including a systems programming language (Go, Python) and a solid understanding of data structures and algorithms.

Ways to stand out from the crowd:

• Technical competency in managing and automating large-scale distributed systems independent of cloud providers. Advanced hands-on experience and deep understanding of cluster management systems (Kubernetes, Slurm, Bright Cluster Manager)
• Proven operational excellence in maintaining reliable and performant AI infrastructure.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you are creative and autonomous, we want to hear from you!

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

Originally posted on Himalayas