Staff Production Engineer Public Sector Jobs

P-1477 Databricks is transforming how it builds and operates People Technology — moving from traditional SaaS configuration toward an AI-native, agentic stack. You'll be the technical anchor of the People Tech pod, driving the architectural shift from workflow automation to autonomous, multi-agent systems that power HR, recruiting, workforce analytics, and employee experience at scale. This is a rare opportunity to reimagine a critical enterprise domain from the ground up using the very data and AI platform Databricks sells to the world. What you'll do Architect and build agentic systems that automate and augment People Tech workflows — onboarding, offboarding, comp analysis, policy Q&A, HR service delivery — using LLM orchestration frameworks (LangGraph, AutoGen, or equivalent). Define the agentic platform strategy for the pod: agent design patterns, tool-calling conventions, retrieval-augmented pipelines, evaluation frameworks, and human-in-the-loop guardrails. Integrate People Tech systems (Workday, Greenhouse, ADP etc.) as agent-accessible tools and data sources via Databricks Unity Catalog and MCP-style interfaces. Set the technical bar for the pod — reviewing designs, establishing engineering standards, and leading architectural reviews across the People Tech roadmap. Influence peers and stakeholders: translate agentic capability into business outcomes for People, Legal, and Finance partners, and mentor engineers in the pod on AI-first thinking. What we're looking for 8+ years of software engineering experience, with at least 2 years building production LLM or agentic applications (agents, RAG pipelines, tool-use, multi-agent orchestration). Deep fluency in Python and experience with agentic frameworks — LangChain/LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar. Strong command of enterprise integration patterns: REST/GraphQL APIs, event-driven architecture, and connecting SaaS HR/HCM platforms programmatically. Experience with data platforms — Data

About the Role Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications — serving speech-to-text and text-to-speech models with best-in-class latency and reliability. We're looking for a Staff ML Engineer to drive the model serving layer for voice workloads. You'll work hands-on with inference engines like TRT-LLM and SGLang to optimize how we serve models like Whisper, Parakeet, Orpheus, and Kokoro — pushing latency and throughput to the frontier. You'll profile GPU utilization, design batching strategies for streaming audio, and ensure new model architectures can go from research to production quickly. This is a foundational hire on a small, high-impact team. Voice inference has unique challenges — streaming audio, tokenization, real-time latency budgets — that require dedicated ML engineering focus. You'll shape how Together serves voice models as the industry moves from pipeline architectures (ASR → LLM → TTS) toward end-to-end speech-to-speech. Own the model serving stack that powers Together's voice platform across STT, TTS, and speech-to-speech. Work directly with state-of-the-art accelerators (H100s, H200s, B200s) to optimize voice model inference. Collaborate with model partners (Cartesia, Deepgram, Rime, and others) to bring their models to production on Together's infrastructure. Build quality evaluation frameworks that guide model selection for customers and inform the roadmap. Join a small, early-stage team with outsized impact on a fast-growing product area. Responsibilities Own the voice inference roadmap end-to-end — define and execute the technical strategy for optimizing STT, TTS, and speech-to-speech models across Together's infrastructure, with a clear-eyed view of where the field is heading and how to position the platform ahead of it. Drive best-in-class inference performance — architect and implement systems targeting leading

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Staff Software Engineer - Container Platform (Menlo Park) About the Role We build the foundational container platform that runs Snowflake's production, AI/ML, and CI workloads across AWS, Azure, and GCP, including a rapidly growing AI/ML footprint. Hundreds of large Kubernetes clusters under management and growing. The work is to make that fleet reliable, automated, and invisible to the thousands of engineers building on top of it. This is a staff-level role on a senior, high-performing platform team. You'll own hard problems end to end, drive technical direction across teams, and build the automation and platform abstractions that make operating at this scale sustainable. There is significant unsolved work ahead: improving the developer experience for thousands of internal engineers and continuing to scale the platform to meet Snowflake's growth. What You'll Do Own the design and delivery of large, complex platform initiatives spanning cluster lifecycle management, multi-cloud automation, and internal developer tooling. Identify and drive cross-team technical improvements across the platform, from architecture through adoption. Make and defend architectural trade-offs grounded in reliability, scalability, and operational reality. Act as a technical anchor for the team, dev

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media, telecommunications, and government to build production AI agents that automate complex workflows, reason over enterprise knowledge, and operate safely at scale. The Opportunity The hardest part of enterprise AI isn't building a great model—it's building AI systems that reliably operate inside complex production environments. As a Staff Frontier Agent Engineer (Forward Deployed Engineering) , you'll work directly with strategic enterprise customers to architect, integrate, deploy, and operate production AI systems. You'll combine modern software engineering, distributed systems, cloud infrastructure, and frontier AI technologies to transform cutting-edge models into reliable enterprise software. Unlike traditional infrastructure or platform roles, you'll work at the intersection of AI and enterprise engineering. You'll design production agent architectures, integrate with customer systems, deploy AI into mission-critical workflows, and help shape the engineering best practices for the next generation of enterprise AI. If you enjoy solving difficult systems problems, rapidly prototyping new AI capabilities, and bringing frontier AI into production, you'll fit right in. What You'll Build Enterprise AI Systems Architect and deploy production AI systems that integrate seamlessly into complex enterprise environments, including cloud platforms, data warehouses, internal APIs, business applications, and proprietary software systems. Design scalable agent architectures that combine LLMs, retrieval, memory, tools, structured knowledge, and enterprise data into reliable production workfl

Staff Software Engineer - AI Research Infrastructure P-1215 At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions. The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all. Job Description As a Staff Software Engineer, AI Research Infrastructure, you will be developing and running the research stack that powers Databricks AI Research. You will design and build services that schedule, orchestrate, and observe large‑scale training and inference experiment workloads across thousands of GPUs, improve our dev tooling and ensure that researchers can iterate quickly without sacrificing reliability, efficiency, or security. You’ll partner closely with research scientists, ML engineers, and platform teams to turn experimental workloads into robust, repeatable pipelines, and to push the limits of what our infrastructure can support. The Impact you will have As a Staff Software Engineer on the AI Research Infra Team at Databricks, you will: Design and implement infrastructure that supports large‑scale experiments, data processing, and model training (e.g., HPC clusters, GPU fleets, or cloud‑based systems) Enable researchers to go from idea to large‑scale experiment in minutes, not days, by building powerful abstractions for job submission, scheduling, and monitoring. Create tooling that improv

Staff Software Engineer - AI Research Infrastructure P-1215 At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions. The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all. Job Description As a Staff Software Engineer, AI Research Infrastructure, you will be developing and running the research stack that powers Databricks AI Research. You will design and build services that schedule, orchestrate, and observe large‑scale training and inference experiment workloads across thousands of GPUs, improve our dev tooling and ensure that researchers can iterate quickly without sacrificing reliability, efficiency, or security. You’ll partner closely with research scientists, ML engineers, and platform teams to turn experimental workloads into robust, repeatable pipelines, and to push the limits of what our infrastructure can support. The Impact you will have As a Staff Software Engineer on the AI Research Infra Team at Databricks, you will: Design and implement infrastructure that supports large‑scale experiments, data processing, and model training (e.g., HPC clusters, GPU fleets, or cloud‑based systems) Enable researchers to go from idea to large‑scale experiment in minutes, not days, by building powerful abstractions for job submission, scheduling, and monitoring. Create tooling that improv

Senior: PLN 260,400 - 352,200 Staff PLN 350,700 - 474,400 Subject to alignment to the responsibilities and duties of the role - we currently have multiple positions available at both Senior and Staff level. About the job Build the quality foundations for Kubernetes systems that power next-generation AI compute. As a Staff QA Engineer, you will validate the workload management stack for new AI accelerator hardware. You will help ensure our Kubernetes integrations are robust, scalable and ready for production. Your work will shape how accelerators are scheduled, orchestrated and used across distributed environments. You will test the systems that make complex AI compute infrastructure reliable for real users. You will design automated test suites, build system and integration tests, and improve CI/CD quality practices. You will also debug issues across Kubernetes, infrastructure and applications. This role is for someone who wants to raise engineering quality across a deeply technical platform. The team and culture You will join the Workload Management team, working closely with software engineers and infrastructure specialists. The work is hands-on, systems-focused and driven by clear technical ownership. Quality is built early here, not checked at the end. You will influence test strategy, validation plans and automation practices across the development lifecycle. The team moves through open technical discussion and evidence-based decisions. You will mentor others, speak up on risk and help turn complex systems into dependable products. What we’re looking for Strong Python programming experience, with a focus on automation and test engineering Hands-on experience with Robot Framework or similar automation frameworks Experience testing cloud-native, containerised or distributed systems Strong Linux understanding and confidence debugging across multiple system layers Experience with CI/CD systems such as GitLab CI or GitHub Actions Ability to define quality standards,

Come join the Server Ingress Security team, where we are rearchitecting MongoDB Server’s ingress networking to make MongoDB clusters even more secure. This new team is building the Atlas Network Protection layer, a set of performant, security-critical services that harden MongoDB's pre-authentication attack surface and provides the ability to respond rapidly to emergent threats. We are looking for talented Staff Engineers to join the team and be founding members, where you will play a crucial role in our multi-year roadmap. Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to be a key technical leader on a collaborative team that applies security and systems engineering fundamentals to protect a popular database at scale, join us! We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. Candidate Profile 10+ years of experience building production-quality systems software with a large user base, robust design structure, and rigorous code quality Experience with large backend/compiled codebases and performance-sensitive software, preferably in Rust Bonus points for experience working hands-on in security-sensitive or networking-adjacent domains Strong systems fundamentals, including multi-threaded programming and performance profiling. Bonus points for: Understanding of network protocols, TLS, and connection lifecycle management. Familiarity with security concepts such as attack surface reduction, input validation, memory safety, and defense-in-depth architectures. Excellent verbal and written technical communication skills for communicating to a wide variety of audiences ranging from junior engineers to executive stakeholder Strong mentorship skills, and excitement about leveling up your peers and teammates through coaching, feedback, and enablement Strong time management skills and the ability to realistically assess project complexity B.Sc. in Computer Science or a related

P-1652 At Databricks, we’re passionate about enabling data teams to solve the world’s toughest problems — from advancing the future of transportation to accelerating medical breakthroughs. We do this by building and operating the world’s best data and AI infrastructure platform so our customers can turn deep data insights into business impact. Founded by engineers and driven by customer obsession, Databricks takes pride in tackling hard technical challenges — from designing next-generation UI/UX for working with data, to scaling our services and infrastructure across millions of virtual machines. And we’re only getting started. As the Staff Technical Lead (TL) for Customer Experience Intelligence, you will architect and deliver Databricks' AI-native vertical workflow platform. CXI is building intelligent systems that orchestrate AI agents, humans, and enterprise tools into end-to-end operational workflows. Support is our first production domain and the platform is designed to expand across multiple domains such as IT, Security, Legal, Marketing, and other knowledge-worker workflows, with a roadmap toward broader productization. The Impact You Will Have: Architect the Agentic Ecosystem: Contribute to the technical vision, core infrastructure, and backend architecture for Databricks’ next-generation Enterprise Agentic Framework. Scale across multiple domains: Build a vertical modular, multi-tenant agent platform initially optimized for Customer Support, but natively designed to expand into other domains such as IT, Security, Compliance, Marketing, HR, Legal and all ticket based workflows across the company. Engineered Reliability: Drive rapid, iterative backend development while upholding strict quality, safety, throughput, and reliability standards for agentic-based systems. Orchestrate Complex Workflows: Design state-machine and agentic workflows that seamlessly evolve from human-in-the-loop validation to fully automated execution. Enterprise-Grade Observabilit

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is seeking talented and experienced Software Engineers to join our Continuous Integration (CI) team within the Developer Productivity organization. The CI team is responsible for the infrastructure that enables hundreds of engineers to ship code safely and efficiently to production. By joining this team, you'll have a direct impact on the velocity and reliability of Anthropic's research and product development. The CI team manages Anthropic's continuous integration system, which includes: CI infrastructure for automated testing and code quality assurance across our monorepo, designed to scale with rapid growth Test infrastructure that runs on Kubernetes clusters across multiple cloud providers, handling intelligent test selection, execution, and reporting for a large and complex test suite Merge queue management and complex branching strategies that ensure code quality at scale CI tooling and automation to improve developer productivity and reduce operational overhead Responsibilities Design and build highly reliable, scalable CI infrastructure that supports thousands of daily builds across multiple cloud providers Develop intelligent test selection systems that reduce CI time while maintaining code quality Build and improve incident response automation, including cluster load shedding, automatic recovery, and observability tooling Improve test infrastructure reliability through flake detection, quarantine systems, and test state management You may be a good fit if you Have 10+ years of relevant industry experience building and operating large-scale CI/CD systems Have deep experience with CI orchestration tool

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. Replit is building the world’s most accessible AI coding agent. Replit Agent can be used by anybody to bring their ideas to life. Whether it’s an app for yourself, the next great startup idea, or a tool to make you more productive at work, Replit Agent can help build it. Replit builds complete apps better than anybody thanks to our full suite of services that handle app integrations, storage, hosting, analytics, and more. We don’t just build apps in development, we handle the full lifecycle into production and beyond. About the role: Help power the development of Replit Agent as a technical leader for the Replit Cloud organization. You will report to the Vice President of Engineering. The Replit Cloud team builds Replit’s first party cloud infrastructure so users can build, scale, and succeed entirely on Replit. They manage databases, application storage, app publishing and hosting, development/production environment splitting, custom domains, and more. By having a set of first party services that integrate seamlessly, you will power one of Replit’s key product differentiators. You will: Help lead major projects, either by taking new products from 0->1 or doubling down on our first party primitives to keep winning users. Work closely with designers and product managers, to quickly iterate on Replit Cloud to continually grow and improve the product. Identify the hardest technical and/or quality problems holding us back, and then build solutions. Mentor and develop new senior engineers to help grow the team. Ship product and build infrastructure as a true full stack builder using: TypeScript, React, CSS, Postgres, Go, and Terraform. Examples of what you could do: Leverage our unique cloud infrastructure to build diffe

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborate with cross-functional teams to define, design, and deliver new features. Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades. Present technical information to teams and stakeholders, providing

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We're looking for a Software Engineer to join the team building Claude Security. In this role, you'll take new security capabilities in frontier models and turn them into products that customers can rely on, working across the full stack from early prototype through production. This role sits close to both research and go-to-market. You'll work with researchers on the team to understand what the models can do and where they fall short, and with customers and partners to understand which problems are worth solving for them. You'll be expected to form your own view from both and to own significant pieces of the roadmap, including deciding what not to pursue. The right candidate is a strong generalist engineer with the technical depth to engage with research, the product instincts to know what's worth building, and the drive to move fast. Prior security experience is useful but not required; range across the stack and good judgment about what to build matter more. Responsibilities Build and ship user-facing and/or backend features for Claude Security Build the agent loops, tool integrations, and enabling infrastructure for cybersecurity products Collaborate tightly with product managers and go-to-market to understand user needs, shape feature scope, and make informed tradeoffs as you build Iterate quickly based on user feedback and internal testing, improving the experience on a continuous basis Collaborate with research teams to identify and develop new model capabilities for security applications You may be a good fit if you: Contribute across the stack, from front-end UI to back-end infrastructure Are proficient in Type

P-1285 About This Role As a staff software engineer for GenAI inference, you will lead the architecture, development, and optimization of the inference engine that powers Databricks Foundation Model API.. You’ll bridge research advances and production demands, ensuring high throughput, low latency, and robust scaling. Your work will encompass the full GenAI inference stack: kernels, runtimes, orchestration, memory, and integration with frameworks and orchestration systems. What You Will Do Own and drive the architecture, design, and implementation of the inference engine, and collaborate on model-serving stack optimized for large-scale LLMs inference Partner closely with researchers to bring new model architectures or features (sparsity, activation compression, mixture-of-experts) into the engine Lead the end-to-end optimization for latency, throughput, memory efficiency, and hardware utilization across GPUs, and accelerators Define and guide standards to build and maintain instrumentation, profiling, and tracing tooling to uncover bottlenecks and guide optimizations Architect scalable routing, batching, scheduling, memory management, and dynamic loading mechanisms for inference workloads Ensure reliability, reproducibility, and fault tolerance in the inference pipelines, including A/B launches, rollback, and model versioning Collaborate cross-functionally on Integrating with federated, distributed inference infrastructure – orchestrate across nodes, balance load, handle communication overhead Drive cross-team collaboration: with platform engineers, cloud infrastructure, and security/compliance teams Represent the team externally through benchmarks, whitepapers, and open-source contributions What We Look For BS/MS/PhD in Computer Science, or a related field Strong software engineering background (6+ years or equivalent) in performance-critical systems Proven track record of owning complex system components and driving architectural decisions end-to-end Deep understa

About Bazaarvoice At Bazaarvoice, we create smart shopping experiences. Through our expansive global network, product-passionate community & enterprise technology, we connect thousands of brands and retailers with billions of consumers. Our solutions enable brands to connect with consumers and collect valuable user-generated content, at an unprecedented scale. This content achieves global reach by leveraging our extensive and ever-expanding retail, social & search syndication network. And we make it easy for brands & retailers to gain valuable business insights from real-time consumer feedback with intuitive tools and dashboards. The result is smarter shopping: loyal customers, increased sales, and improved products. The problem we are trying to solve : Brands and retailers struggle to make real connections with consumers. It's a challenge to deliver trustworthy and inspiring content in the moments that matter most during the discovery and purchase cycle. The result? Time and money spent on content that doesn't attract new consumers, convert them, or earn their long-term loyalty. Our brand promise : closing the gap between brands and consumers. Founded in 2005, Bazaarvoice is headquartered in Austin, Texas with offices in North America, Europe, Asia and Australia. It’s official: Bazaarvoice is a Great Place to Work in the US , Australia, India, Lithuania, France, Germany and the UK! The Role: We are seeking a highly experienced and strategic Staff Machine Learning Engineer to join our AI & Data Science team. This is a senior-most individual contributor role where you will be responsible for owning the end-to-end Machine Learning Development Lifecycle (MDLC). You will architect, build, and deploy production-grade, scalable ML systems that transform massive volumes of user-generated content into actionable insights for our customers. This position requires a proven track record of solving complex, unstructured data challenges and a deep expertise in buildi