Senior Distributed Systems Engineer Jobs

About the Opportunity Enabling millions of distributed energy devices to deliver reliable and predictable grid services to the electricity industry requires state-of-the-art forecasting, control systems, optimization algorithms, and data science. As such, EnergyHub seeks to hire a Senior Forecasting and Optimization Engineer to join EnergyHub’s Data Science and Power Systems Intelligence team. As a Senior Forecasting and Optimization Engineer you will work closely with some of the brightest minds in the electricity industry to solve some of the most difficult problems in distributed energy. The algorithms and data systems that you contribute to will be key to enabling a carbon-free distributed energy future. Main Responsibilities: What you’ll do Develop and improve accurate and robust energy forecasting models Develop and improve control and optimization algorithms Design, write, test, and deploy production-grade code for mission-critical forecasting and optimization products and related algorithms Build and use tools and processes to monitor and assess the quality of operational forecasting and optimization models Translate data from one of the largest distributed energy datasets in the electricity industry into actionable insights for electric utilities and other energy industry stakeholders Provide guidance to other engineers and scientists regarding machine learning, forecasting and optimization methods Present results clearly to internal and external stakeholders Collaborate closely with stakeholders inside and outside of EnergyHub including Data Engineering, Client Success, Marketing, Sales, Product, and Market Development teams Other duties as assigned Required Skills and Experience: What you need Passion for enabling a carbon-free, distributed energy future At least five years of experience in machine learning, statistical analysis, data visualization, control systems engineering, and/or mathematical optimization Experience developing data pipelines using la

MongoDB’s Storage Layer Services (SLS) team is re-architecting the MongoDB cloud storage layer and sits at the heart of our next-generation cloud storage architecture. This relatively new team is building performant, multi-tenant distributed storage services that both enhance today’s Atlas storage stack and enable more customer workloads to run more efficiently. We are looking for a talented Senior Software Engineer to join our team as we execute on a multi-year roadmap and prepare to launch and rapidly scale services that handle petabytes of data. Come do some of the most interesting work of your career as we Think Big and Go Far for our customers! This role can be based out of our New York City office (hybrid working model) or remotely in the North America region. What you’ll do Design, build, and operate control plane services powering an elastic and multi-tenant storage layer for thousands of database instances. Solve problems around maintaining high availability and performance during load spikes, hardware failures, cloud provider outages, and other disruptions. Contribute to a culture of operational excellence through dashboards, playbooks, and on-call improvements. Lead complex technical projects from planning through successful deployment with clear stakeholder updates. Partner closely with peers across database, cloud, and infrastructure engineering teams as well as project management to investigate incidents and develop long-term roadmaps. Mentor junior engineers and foster a collaborative team environment. We’re looking for someone with 5+ years of professional software development experience building, deploying, and operating multi-tenant cloud services with a focus on operational excellence. Experience with large backend/compiled codebases, such as Rust or C/C++. Experience with containerization and orchestration platforms (e.g. Kubernetes). Experience with observability tooling (e.g. time series metrics, dashboards). Experience with distributed systems

P-1428 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Training and customizing state-of-the-art AI models is one of the most demanding workloads in computing, and it sits at the heart of Databricks' Mosaic AI mission. AI Runtime (AIR) is our managed platform for large-scale GPU training and fine-tuning. It gives customers on-demand access to fleets of the latest accelerators and a serverless experience that hides the complexity of provisioning, scheduling, and orchestrating multi-node jobs, with the resilience to keep training running for days or weeks across thousands of GPUs. AIR powers the full spectrum of custom training, from fine-tuning open models to pre-training frontier-scale foundation models, for some of the most sophisticated AI teams in the world. As a Senior Software Engineer for AI Runtime, you will play a critical role in building and scaling the systems that make large-scale training fast, reliable, and effortless. You will drive the architecture and evolution of the managed GPU training stack, spanning scheduling and capacity, distributed training performance, fault tolerance, and the developer experience of launching and operating jobs at scale. Beyond hands-on contributions to core systems, you will help shape the technical direction for AIR, mentor other engineers, partner across product, research, and platform teams, and contribute to the initiatives that expand the technical and business impact of custom training at Databricks. Check out our recent blog post: Introducing AI Runtime: Scalable, serverless NVIDIA GPUs on Databricks for training and finetuning The impact you will have: Drive the architecture and evolu

NVIDIA is building the software foundation for the next generation of AI infrastructure. As AI workloads continue to evolve, Kubernetes and the cloud-native ecosystem must evolve with them. Our team’s mission is to make Kubernetes the best platform for AI workloads. We work upstream with the Kubernetes and CNCF communities to design new APIs, build production-grade implementations, and shape the future of cloud-native infrastructure for AI. As a Senior Software Engineer, you'll tackle the most challenging problems at the intersection of Kubernetes, distributed systems, and AI infrastructure. What you'll be doing Design, implement, and upstream new capabilities for Kubernetes and CNCF projects. Collaborate with engineering teams across NVIDIA to identify AI infrastructure challenges and solve them through upstream innovation. Work closely with Kubernetes SIGs, Working Groups, and the broader open-source community to design and implement new capabilities. Participate in architecture discussions, API design, technical proposals, and code reviews. Build reliable, scalable infrastructure software for next-generation AI workloads. Write clear technical documentation and design proposals. What we need to see B.Sc/M.Sc or higher in Computer Science, Computer Engineering, or a related field or equivalent practical experience. 5+ years of software engineering experience building distributed systems, cloud infrastructure, or platform software. Deep understanding of Kubernetes and the cloud-native ecosystem. Experience extending, building, or contributing to Kuberne

The NVIDIA DGXC Data Services team builds cloud-native systems, frameworks, and services for managing data across hybrid and multi-cloud infrastructure. We are building the next-generation data and storage infrastructure to solve some of the hardest problems in AI: storage, access, ingestion, governance, observability, and data management for exabyte-scale, high-performance GPU-based training and inference jobs. Our work gives NVIDIA teams the foundational capabilities they need to build, train, deploy, and operate AI products at scale without reinventing critical data infrastructure for every workload. What you will be doing: Build cloud-native data and storage services for hybrid and multi-cloud infrastructure, including dataset discovery, ingestion, governance, checkpointing, observability, and low-latency access. Develop scalable cloud-native services and APIs that support exabyte-scale, high-performance GPU training and inference workflows. Work closely with product managers, internal AI teams, platform teams, and partner engineering teams to understand requirements and turn them into reliable production systems. Collaborate with SRE, operations, and support teams to improve service reliability, performance, observability, on-call readiness, and operational scale. Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, and verification. What we need to see: BS in Computer Science, Information Systems, Computer Engineering, or equivalent experience, with 5+ years of software engineering experience. Strong foundation in algorithms, data structures, distributed systems, and practi

About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About The Team Snorkel's AI Platform organization builds the infrastructure and systems that power AI development at scale - synthetic data generation, evaluation, agentic workflows, simulation environments, LLM infrastructure, and distributed compute. Our platform enables engineering and research teams to rapidly experiment with models and agents, measure their behavior, and turn successful experiments into reliable production systems. We're a small team operating at the intersection of distributed systems and applied AI, and we're in the middle of a foundational shift toward agent-first workflows where models interact with tools, environments, data, and other agents over long-running trajectories. The systems we build need to make these inherently non-deterministic workloads observable, reproducible, measurable, and scalable. You will help define how we do that. About The Role We're looking for Software Engineers at Senior / Staff levels who combine strong software and distributed systems fundamentals with experience operating AI systems in production. You'll build the infrastructure that lets teams create, experiment with, evaluate, and operate LLM and agentic workloads at significant scale - from synthetic data and evaluation pipelines to simulation environments, orchestration systems, and LLM infrastructure. You'll work on systems where correctness is not defined by a single deterministic output. Instead, you'll build the infrastructure neede

SonicWall is a cybersecurity forerunner with more than 30 years of expertise and is recognized as a leading partner-first company, ensuring our partners and their customers are never alone in the fight against cybercrime. With the ability to build, scale and manage security across the cloud, hybrid and traditional environments in real-time, SonicWall provides relentless security against the most evasive cyberattacks across endless exposure points for increasingly remote, mobile and cloud-enabled users. With its own threat research center, SonicWall can quickly and economically provide purpose-built security solutions to enable any organization—enterprise, government agencies and SMBs—around the world. For more information, visit www.sonicwall.com or follow us on Twitter , LinkedIn , Facebook and Instagram . As a Software Dev Senior Engineer , you will own the reliability, scalability, and operational excellence of our Cloud-based services. You will define and enforce reliability standards, drive the adoption of SRE practices across engineering teams, and build the systems and tooling that keep our production infrastructure healthy. We follow a DevOps model: Development and Operations teams are integrated, and the SRE function acts as the reliability layer — setting Service Level Objectives, managing error budgets, and continuously reducing toil through engineering. Key Responsibilities: Define, publish, and continuously refine Service Level Indicators (SLIs), Service Level Objectives (SLOs), and Service Level Agreements (SLAs ) for all critical services, partnering with product and engineering leadership. Own the error budget framework: track consumption, enforce error budget policies, and drive reliability investments when budgets are at risk. Lead the design and implementation of comprehensive observability platforms — metrics, structured logging, and distributed tracing — to ensure full visibility into pro

PagerDuty, Inc. (NYSE: PD) is the global leader in AI-first digital operations. By automatically detecting, diagnosing, and remediating issues, the PagerDuty Platform orchestrates AI agents and automated workflows with context from over 750 integrations. Trusted by approximately two-thirds of the Fortune 100 and nearly half of the Fortune 500, PagerDuty is the industry standard for organizations scaling resilient, autonomous operations. Notable customers include Chipotle, Cloudflare, Docusign, Fox, Nvidia, Salesforce, Spotify, Zoom and more. We are growing rapidly and hiring top talent with leading AI skills across engineering, sales, product, marketing, and beyond as we build the leading digital operations platform. About the role PagerDuty’s Operations Cloud runs on a platform that ingests billions of signals and turns them into real-time action for thousands of customers. We’re looking for a Senior AI/ML Engineer who lives at the intersection of two disciplines: large-scale distributed systems and applied AI. In this role you will design and ship AI systems that run in production at PagerDuty’s scale — powering Incident Management AI Agents, event intelligence, and the LLM-powered capabilities embedded across our platform. You’ll own the full lifecycle, from framing the problem to serving reliably at scale. We are looking for a candidate who is genuinely passionate about building with modern AI — LLMs, agents, and retrieval — but grounded in the realities of building resilient, high-throughput systems. What you’ll do Design and build AI-powered features — LLM agents, retrieval, and event intelligence — that operate on high-volume, real-time event streams, from problem framing through production deployment and monitoring. Architect and own the systems behind them: agent and prompt orchestration, retrieval pipelines, tool/API integrations, and low-latency inference and evaluation at scale. Reason about consistency, throughput, fault tolerance, and cost acros

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform providing APIs for knowledge retrieval, inference, evaluation, and more. We are seeking a strong Senior Full-Stack Engineer to help us build, scale, and refine our rapidly growing product. The ideal candidate is deeply grounded in software engineering best practices and experienced in developing and scaling modern web applications end-to-end. You will work across the stack—from React/TypeScript frontends to Python-based backends—while integrating with LLMs and machine learning systems. You will solve complex challenges in scalability, reliability, and product experience while owning significant product areas in a fast-paced environment. What You’ll Do Own major full-stack product areas , driving features from design through production deployment. Build modern frontend experiences using React and TypeScript, ensuring performance, usability, and responsiveness. Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components. Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences. Deliver experiments and new features quickly , maintaining high quality and tight feedback loops with customers. Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP. Adapt quickly —learning new technologies, frameworks, and tools as needed across the stack. Ideal Experience 5+ years of full-time engineering experience , post-graduation. Strong experience developing full-stack applications using React, TypeScript, and Python . Experience scaling or shipping products at high-growth startups . Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (tinkering or production experience welcome). Proficiency with SQL and modern API development. Experience with Kubernetes , containerization, and microservice architectures. Experience working with at leas

About the Job Turn complex AI workload signals into faster, more efficient systems at data center scale. As a Senior AI Performance Engineer, you will analyze and optimize AI training and inference workloads across large-scale distributed systems. Your work will connect compute, memory, communication and software behavior. You will own complex performance investigations from problem definition through validation. You will turn profiling, benchmarking and modeling results into improvements engineers can build from. You will design benchmarks, investigate system bottlenecks and optimize distributed communication software across technologies such as MPI, NCCL, UCX and RDMA. Your work will help Graphcore deliver efficient, reliable AI systems for large-scale deployment. This role gives you rare scope across hardware, software, networking and system architecture. It is based in Austin, Texas. The team and culture The System Engineering Performance team architects, evaluates and optimizes high-performance infrastructure for large-scale data center deployments. The team works across the computing stack to understand real system behavior. Work moves through evidence, ownership and clear technical judgment. You will define investigations, coordinate across teams and validate impact with reliable performance data. Decisions are shaped through benchmarks, models, simulations and practical engineering tradeoffs. The team values engineers who think big, act fast, take responsibility, speak up and lead beyond their own area. What we’re looking for · Strong experience profiling and optimizing AI, machine learning or high-performance computing workloads. · Experience with distributed systems and communication libraries such as MPI, NCCL, UCX or libfabric. · Strong C++ and Python skills, including reliable tools or performance-sensitive software. · Deep understanding of compute, memory and communication behavior in large-scale systems. · Ability to own complex technical work and coo

About DevRev At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries. About the role: We are looking for a Senior Data Engineer to help build and evolve the data platform that powers critical business decisions and customer-facing experiences. You will own significant parts of our data architecture that is main powerhouse of DevRev Computer’s memory for accurate and efficient Answers. As a part of data team, you will design and operate scalable data systems, and work closely with Software Engineering, AI Agent teams, Data Science, and Product teams to turn complex data requirements into reliable, high-quality data products. This role is ideal for an experienced engineer who enjoys solving challenging problems involving large-scale data, distributed systems, database architecture, and performance optimization . You will have significant technical ownership and the opportunity to influence the direction of our agentic data platform while helping raise the engineering bar across the team. What you'll do: Own data architecture for large-scale, high-impact projects, making thoughtful tradeoffs across scalability, reliability, performance, maintainability, and operational cost. Design, build, and operate scalable data pipelines and data systems that reliably ingest, transform, store, and se

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. Senior Software Engineer, Backend About the team + role We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. Robinhood’s engineering organization spans Crypto, Brokerage, and Core Engineering, each responsible for systems that are foundational to how customers invest and manage their money! These teams build and operate platforms for trading, custody, ledgers, reporting, payments, and shared infrastructure, with a strong focus on correctness, reliability, and customer trust. Engineers partner closely with product, design, data, and infrastructure teams to deliver software that performs at scale. As a Senior Software Engineer , you will design and build large-scale distributed systems that support real-time trading, balances, and platform capabilities. You will lead technically complex projects, contribute to architectural decisions, and collaborate with frontend and data partners to deliver well-structured APIs. Your work will directly influence system performance, operational safety, and long-term maintainability across core Robinhood products. This role is based in our Menlo Park, CA and New York, NY offices, with hybrid attendance expected at least 3 days per week. At Robinhood, we believe in the power of in-person work to accelerate progr

Asana’s rapid growth brings new challenges in keeping our systems fast, reliable, and resilient. As our product evolves, we’re making a major investment in reliability – and building a brand new SRE team in Warsaw is a key part of that strategy. This is your chance to help shape it from day one. This isn’t a traditional “ops” role – we’re looking for strong software engineers who are passionate about building reliable, distributed systems. You’ll work closely with a small SRE team in San Francisco, infrastructure engineers in Reykjavik, and an established infrastructure team in Warsaw. Warsaw will be a significant hub for our future infrastructure engineering and operations. As one of the first engineers here, you’ll have a real say in how we build reliable infrastructure, manage incidents, and support the rest of the company. This role is based in our Warsaw office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements. We offer a Contract of Employment (UoP) for our employees in Poland. What you’ll achieve Influence the future of Asana’s SRE practice, especially as we grow the Warsaw team. Lead reliability-focused projects across our stack – from infrastructure to tooling to incident response. Define and implement Asana’s incident management process – we’re investing here, and you’ll help shape how it works. Build internal platforms and frameworks that help other teams improve the reliability of their services. Be part of (and help shape) a sustainable on-call rotation – shared across teams in Warsaw, San Francisco, and Reykjavik. On average, we handle ~1 page per day, but it’s not constant, and we care about keeping things sane. Work with our stack: AWS, Kubernetes (EKS), Datadog, MySQL (RDS), ElasticSearch (OpenSearch), Redis

We are hiring a Senior AI Engineer to build and operate production AI systems and infrastructure. In this role, you will work on AI agents, MCP servers, agent evaluation, and Temporal-based workflow frameworks. This is a hands-on engineering role for someone who can move between backend systems, AI application development, deployment, and production support. You will help build reliable services and frameworks that make AI agents usable, measurable, and dependable in production. What you’ll be doing: Build and deploy AI agents that use tools, call services, manage context, and execute multi-step tasks. Develop and maintain MCP servers and tool integrations used by internal AI systems. Build workflow infrastructure using Temporal or similar orchestration frameworks. Design and implement agent evaluation flows, test suites, quality metrics, and feedback loops. Design backend services, APIs, persistence layers, and platform components for AI applications. Work with SQL and NoSQL databases, queues, distributed systems, and cloud-native infrastructure. Build CI/CD pipelines, Docker images, Kubernetes deployments, monitoring, and operational tooling. Debug production issues across services, workflows, agents, tools, models, and infrastructure. Collaborate with engineering, product, infrastructure, and data science teams to turn requirements into reliable systems. What we need to see: 5+ years of experience and a practical understanding of how AI agents are built, including tool use, state, context, and multi-step execution. Bachelors degree or equivalent experience. Experience with at least one open-source agent or LLM application framework, such as LangChain/LangGraph. Strong software engineering background, especially in backend development. Experience with distributed systems, workflow orchestration, and prod

We are looking for a Sr. Engineer to design, build, and scale the infrastructure powering NVIDIA’s AI agent ecosystem. You will work at the intersection of distributed systems, developer platforms, and agentic AI — building the foundational services that enable teams across the company to develop, deploy, orchestrate, and operate autonomous AI agents at production scale. What you will be doing: Build and develop platform services that manage the full agent lifecycle from registration through deployment, execution, and teardown Architect multi-tenant Kubernetes execution environments with pod lifecycle management, per-tenant namespace isolation, persistent storage, admission policy enforcement, and identity propagation Develop and maintain automated CI/CD pipelines using GitLab CI and ArgoCD, including reusable pipeline templates and deployment blueprints that standardize how agents are built across teams Build framework-agnostic infrastructure supporting multiple agent SDKs and harnesses — lifecycle hooks, skills configuration, memory services, and OTEL instrumentation — so teams can onboard new agent frameworks without platform changes Build and operate Kafka-based message pipelines and real-time event streaming using Redis PubSub and SSE Develop data ingestion pipelines, access interfaces, and storage layers that power AI agent knowledge and context Implement session management for state persistence, conversation history, and agent recovery across sessions Develop multi-layer auth using OAuth 2.0, JWT validation, token exchange, and gateway integration, and manage secrets lifecycle with Vault (provisioning, rotation, container injection) Partner with security teams on compliance, access controls, and approval workflows for agent operations What we need to see: Bachelor's or Master's degree in Computer Science, Engineering, or