Staff Production Engineer Public Sector Jobs

Altana is the network for trusted trade. Our AI-powered product network empowers governments and businesses to build a more resilient and secure global economy while keeping trade flowing. The Opportunity at Altana The Implementation team is the tip of the spear in getting Altana's platform into production inside our customers' businesses. We own the path from signed contract to realized value: standing up integrations, wiring Altana into the customer's existing business processes, and making sure the insight we deliver actually changes decisions on the customer's side. We are a delivery organization with a technical core. We work directly with customer stakeholders — from trade compliance analysts to enterprise IT — and we work just as closely with Altana's engineering, data science, and product teams to translate what we learn in the field into what gets built next. You Will Design and deploy agentic AI systems Design, build, and deploy agentic AI workflows — multi-step agents, tool and function calling, and automations — that power the customer's business processes and act on real customer data Ground agents in customer context: connect them to the right data sources, APIs, and systems of record, and define the tools, permissions, and guardrails they operate within Write and refine the prompts, system instructions, and evaluation criteria that make an agent reliable enough to trust in production Build the orchestration and human-in-the-loop checkpoints that keep agentic workflows safe, auditable, and correctable in a customer's environment Monitor, evaluate, and iterate on deployed processes — tracking accuracy, cost, and latency, and tuning them as the customer's data and needs evolve Own technology implementation and delivery Lead customer implementations end to end: scoping, configuration, integration, validation, go-live, and handoff to steady-state support Configure and deploy Altana's platform capabilities against real customer data and real customer

Altana is the network for trusted trade. Our AI-powered product network empowers governments and businesses to build a more resilient and secure global economy while keeping trade flowing. The Opportunity at Altana The Implementation team is the tip of the spear in getting Altana's platform into production inside our customers' businesses. We own the path from signed contract to realized value: standing up integrations, wiring Altana into the customer's existing business processes, and making sure the insight we deliver actually changes decisions on the customer's side. We are a delivery organization with a technical core. We work directly with customer stakeholders — from trade compliance analysts to enterprise IT — and we work just as closely with Altana's engineering, data science, and product teams to translate what we learn in the field into what gets built next. You Will Design and deploy agentic AI systems Design, build, and deploy agentic AI workflows — multi-step agents, tool and function calling, and automations — that power the customer's business processes and act on real customer data Ground agents in customer context: connect them to the right data sources, APIs, and systems of record, and define the tools, permissions, and guardrails they operate within Write and refine the prompts, system instructions, and evaluation criteria that make an agent reliable enough to trust in production Build the orchestration and human-in-the-loop checkpoints that keep agentic workflows safe, auditable, and correctable in a customer's environment Monitor, evaluate, and iterate on deployed processes — tracking accuracy, cost, and latency, and tuning them as the customer's data and needs evolve Own technology implementation and delivery Lead customer implementations end to end: scoping, configuration, integration, validation, go-live, and handoff to steady-state support Configure and deploy Altana's platform capabilities against real customer data and real customer

Altana is the network for trusted trade. Our AI-powered product network empowers governments and businesses to build a more resilient and secure global economy while keeping trade flowing. The Opportunity at Altana The Implementation team is the tip of the spear in getting Altana's platform into production inside our customers' businesses. We own the path from signed contract to realized value: standing up integrations, wiring Altana into the customer's existing business processes, and making sure the insight we deliver actually changes decisions on the customer's side. We are a delivery organization with a technical core. We work directly with customer stakeholders — from trade compliance analysts to enterprise IT — and we work just as closely with Altana's engineering, data science, and product teams to translate what we learn in the field into what gets built next. You Will Design and deploy agentic AI systems Design, build, and deploy agentic AI workflows — multi-step agents, tool and function calling, and automations — that power the customer's business processes and act on real customer data Ground agents in customer context: connect them to the right data sources, APIs, and systems of record, and define the tools, permissions, and guardrails they operate within Write and refine the prompts, system instructions, and evaluation criteria that make an agent reliable enough to trust in production Build the orchestration and human-in-the-loop checkpoints that keep agentic workflows safe, auditable, and correctable in a customer's environment Monitor, evaluate, and iterate on deployed processes — tracking accuracy, cost, and latency, and tuning them as the customer's data and needs evolve Own technology implementation and delivery Lead customer implementations end to end: scoping, configuration, integration, validation, go-live, and handoff to steady-state support Configure and deploy Altana's platform capabilities against real customer data and real customer

About the job Shape how Graphcore products move from hardware design into reliable volume manufacturing. As Staff Manufacturing Product Engineer, you will take a leading role in supporting NPI development and volume production across complex hardware products. You will connect design, test, quality and supply chain decisions with real manufacturing outcomes. Your work will help ensure products are manufacturable, resilient and ready for supplier capability. You will provide DfM feedback that improves PCB and system design before issues reach production. You will work closely with contract manufacturers, especially during NPI and early volume manufacture. You will drive yield improvement, analyse production data and resolve L6 manufacturing issues. This role suits someone who enjoys practical engineering ownership across design and production. You will travel to Taiwan and work close to suppliers shaping next generation manufacturing technologies. The team and culture You will join the Manufacturing and Technology Process team within Operations. The team works across Bristol, Cambridge and Taiwan, close to foundry, package assembly and PCBA partners. Work happens through clear ownership, supplier engagement and fast feedback into design teams. You will speak up early when manufacturability, yield or capability needs attention. The team values evidence, responsibility and strong cross-regional relationships. Decisions are made through engineering judgement, data and direct accountability for manufacturing performance. What we're looking for · Strong fault diagnosis, problem solving and failure analysis skills, including ICT to SMT debug · Thorough understanding of Automated surface mount assembly processes and manufacturing methodologies · Working knowledge of L10 mechanical design and system build, ideally for HPC products · Ability to connect silicon, package and PCB interactions into clear DfM feedback · Experienced in statistical analysis tools (e.g JMP, SQL, Pyth

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Staff Machine Learning Engineer, CX Intelligence CEE Intelligence (CEEI) is the ML and intelligence layer for Coinbase's customer engagement ecosystem, building customer intelligence, evaluation systems, routing and classification models, safety guardrails, and decisioning capabilities that power Help Center, chat, voice, agent tooling, and other customer support runtimes. As a Staff Machine Learning Engineer, you'll lead the design and delivery of production ML systems across the org, shaping technical strategy, building scalable intelligence capabilities, and partnering with product and engineering stakeholders to improve resolution quality, automation coverage, safety, and customer experience. What you'll do: Own the design and delivery of production ML systems, applying LLMs, deep learning, graph neural networks, and classical ML techniques to solve complex customer experience problems. Partner with leadership and cross-functional stakeholders to define strategic roadmaps and translate vision into quarterly execution plans with measurable outcomes. Lead high-impact ML projects end-to-end, from architecture through production, managing priorities, risks, and dependencies. Build scalable, secure, and reliable ML systems, evaluation pipelines, and data workflows using high-quality, well-tested Python code. Mentor engineers and establish team-wide standards fo

About SingleStore SingleStore delivers a real-time, distributed SQL database that unifies transactional and analytical workloads. Our engineers build cloud-native software for some of the world’s most demanding data-intensive applications, working in a fast-moving environment where teams own their work end to end and partner closely across Product and customer-facing organisations. About the Flow team SingleStore Flow is an enterprise data migration and integration product that helps customers move data into SingleStore reliably and at scale. The team builds the systems that support schema transfer, bulk data loading, real-time Change Data Capture (CDC), large-table migrations, and a native experience in SingleStore Helios. Flow spans Java-based engines, source and destination connectors, database internals, performance and memory management, Helios services and APIs, observability, test automation, Flow AI Agent and signed production release delivery. The product works across heterogeneous database environments, including MySQL, PostgreSQL, Oracle, SQL Server, MongoDB, SAP HANA, Snowflake, Salesforce, and SingleStore-as-a-source. Position Overview We are looking for a Staff Engineer to provide technical leadership for Flow’s end-to-end data path from source systems and CDC through migration engines, APIs, Helios, and the customer experience. This is a hands-on individual contributor role with broad technical influence. You will own major architectural decisions, lead strategically important and release-defining initiatives, solve complex reliability and data-consistency problems, and help the team build durable systems that customers can trust with their most important migrations. You will remain close to the code while raising the technical bar for design, testing, observability, operational excellence, and AI-assisted engineering. The ideal candidate is a systems-minded engineer who enjoys working across product boundaries, can move comfortably between architectu

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. About our Team: We are seeking an experienced AI Full Stack Engineer to build modern applications where AI is a first-class capability—both in the development workflow and in production systems. This role focuses on designing and integrating AI-powered solutions using custom agents, Model Context Protocol (MCP), and scalable software engineering practices to accelerate development and deliver reliable, production-grade systems. Our team needs additional support to scale with the increased SMAI Data Science footprint and expand software support for Technology Development workflows and AI enablement. Position Overview: We are looking for an AI Full Stack Engineer who builds modern applications using AI as a first-class capability—both as part of the development workflow and the systems we ship. This role goes beyond simply using AI coding assistants. It requires strong understanding of advanced timely creation, vibe scripting, Rework Rate Reduction, and applying Custom Agents with integrations built around MCP or equivalent experience. The goal is to significantly shorten development and feedback cycles by automating routine engineering work, augmenting human decision-making, and embedding intelligence into development workflows and delivered applications. Responsibilities: Contribute to platform enablement, architecture decisions, code reviews, and shared engineering standards; design, build, test, deploy, and operate full stack software solutions while owning features end‑to‑end including system

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. What You’ll Be Doing Design, build, and operate highly scalable, reliable, and secure infrastructure powering our production systems across AWS and GCP. Lead major reliability and modernization initiatives, including container platform migrations (e.g., ECS to EKS/GKE) and microservice enablement across multi-cloud environments. Serve as a technical authority in Kubernetes (EKS and GKE), cloud infrastructure (AWS and GCP), and modern CI/CD practices (GitOps, automation pipelines). Partner with development teams to architect and enable microservice-based applications, ensuring production readiness, scalability, and observability. Implement and manage infrastructure as code (Terraform, Ansible) to automate provisioning, scaling, and configuration management across multiple cloud providers. Drive improvements in observability, performance, and cost efficiency through robust monitoring, logging, and alerting systems that span AWS and GCP. Champion SRE best practices — defining SLOs/SLIs, conducting blameless postmortems, and continuously improving incident response. Lead complex technical projects from conception to completion, managing timelines, and technical dependencies across teams. Mentor engineers across teams, fostering a culture of reliability, automation, and continuous learning. Collaborate with security and compliance partners to ensure infrastructure adheres to best practices and standards (e.g., IAM Federation, Workload Identity). Participate in t

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Job Description The HBM Architecture team develops advanced datapath solutions that enable industry‑leading bandwidth, power efficiency, reliability, and scalability for Micron’s next‑generation High Bandwidth Memory (HBM) products. The team collaborates closely across design, PHY, ECC, verification, layout, and system groups to drive innovative logic‑die and core‑die architectures from concept through production. We are seeking a highly motivated HBM Datapath Architect to architect, design, and optimize high‑speed data paths for next‑generation High Bandwidth Memory (HBM) products! This role focuses on logic‑die and core‑die datapath circuitry, enabling industry‑leading bandwidth, power efficiency, reliability, and scalability across JEDEC and custom HBM solutions. The ideal candidate will work closely with design, PHY, ECC, verification, layout, and system teams to deliver robust datapath designs from concept through silicon bring‑up and production. Responsibilities will include, but are not limited to: Architect and design HBM read and write datapath across core and logic die, including alignment, buffering, timing, and control logic Develop high‑speed, low‑latency datapath circuits supporting multi‑channel HBM architectures and wide internal buses Optimize datapath designs for bandwidth, power, area, and timing closure at advanced technology nodes

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest is seeking a Staff Software Engineer to help evolve the serving platforms that power Ads and Core experiences. You will lead large-scale, low-latency distributed-system initiatives that make our serving stack more performant, reliable, observable, and easier to extend. You will work across Ads and Core engineering teams to define durable platform capabilities, modernize frameworks, and unlock faster product iteration with high confidence in production. What you’ll do: Set technical direction and lead architecture for major serving-platform initiatives across Ads and Core. Build and operate scalable, highly available systems with clear performance, reliability, and efficiency goals. Partner with product, ML, infrastructure, and Core/Ads engineering teams to translate complex requirements into reusable platform capabilities.

At Carbon, our mission goes beyond 3D printing. We are enabling creators everywhere to make what the world needs, right now. Our company is built on the idea that diverse fields of study must come together to solve intractable problems. We have grand ambitions to create technology that will influence industry around the world. You will be joining a diverse team with a vibrant culture, where team success is as important as celebrating individual contributions. Help us change the world and we will help you change yours. Carbon’s Application Engineering team owns the collaboration with visionary partners from concept to production readiness. As a Staff Application Engineer, you are a seasoned technical expert who leads complex, cross-functional programs from concept through production and increasingly shapes the tools, workflows, and technical strategy that scale Carbon’s Application Engineering practice. You operate with a high degree of autonomy, own outcomes across your programs, and build your influence with stakeholders across the company. You thrive in employing your creative problem-solving abilities and growing your depth of expertise across a variety of functional areas (including software, materials, hardware, product development processes, and cross-functional team leadership). You are comfortable leading engagements with external and internal company stakeholders and can handle tough situations with poise and confidence. Role is based in our Sunnyvale, CA office, working minimum 3 days a week (Tues-Thurs) onsite. Occasional travel to customer locations is required, around 10% of the time (domestic and international). Responsibilities Educate and influence customers on Design for DLS best practices and design for manufacturability, including printer operation, materials, design guidelines, software, and post-processing; guide customers through design, aesthetic, and technical tradeoffs that meet production requirements such as cost and man

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: The Safeguards ML Inference Path team designs, builds, and operates the production infrastructure that powers Claude's ML based safety systems. We collaborate closely with safety researchers and inference engineers to bring new classifiers and novel classes of ML defenses to production. We own the research → production transfer of new safety technologies that is on the critical path for every Claude model launch. And we build for scale: serving thousands of ML classifiers, for all requests on the token generation path, and for every platform Claude runs on -- 1P, Bedrock, Vertex, and beyond. We’re growing the team and looking for engineers who have deep expertise in productionizing ML systems. You'll work at the intersection of machine learning, large-scale distributed systems, and AI safety, developing the platforms and tools that enable our safeguards to operate reliably at scale. And your tooling and infrastructure will be used for every model launch, which are becoming more complex, and more frequent. Responsibilities: Design and build scalable ML infrastructure to support real-time safety deployments across our classifier and model ecosystem Build monitoring and observability tools to track classifier performance, data quality, and system health for safety-critical applications Collaborate with research teams to productionize safety research, translating experimental safety techniques into robust, scalable systems Optimize inference latency and throughput for real-time safety evaluations while maintaining high reliability standards Implement automated testing, deployment, and rollback systems for ML models in prod

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: The Safeguards ML Sampling Path team builds and operates the production services that power Claude's safety systems. These services sit on the token generation path across every platform Claude runs on: every request must pass through them, and each millisecond of added latency is wait time for our users. You’ll keep p99 latency flat as traffic grows, build for robustness as dependencies time out or partially fail, and ship changes safely to a system that cannot go down. What you'll do: Design, build, and operate the backend systems that process every token on the generation path for Claude requests, including the streaming contract with the API and inference engines. Own latency and reliability end to end: define and maintain SLOs and error budgets for added latency, time-to-first-token, and availability, and lead incident response and postmortem follow-through. Ship changes to the hot path rapidly but safely — canaried and gradual rollouts, error budget and latency gating, fast rollbacks — and drive per-token performance: chase tail latency and keep cost flat as traffic, models, and checks per request grow. Set technical direction for the sampling path: lead design reviews, make latency, reliability, and cost trade-off calls with the inference and research teams, mentor engineers, and raise the operational bar for the wider Safeguards organization. You may be a good fit if you: Have designed, built, and operated high QPS systems at global scale, and were accountable for them in production: incident response, outages, and postmortem-driven remediation. Have a strong foundation in distributed systems: replication, cons

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Responsibilities Develop, build, and operate production-grade AI agents supporting task automation, decision support, summarization, and human-in-the-loop execution, including the orchestration governing planning, tool use, multi-step state, failure recovery, and escalation to a person. Build and maintain the Model Context Protocol (MCP) and enterprise tool layer that exposes Micron's manufacturing systems and enterprise data to agents as well-scoped tools, resources, and prompts, owning tool contracts, schema and version management, and the reviews that keep every exposed capability auditable. Ground agents in authoritative, versioned proven experience, working with the manufacturing and engineering experts who own the operational rules to translate them into structured knowledge that agents can reason over reliably as the domain evolves. Establish the evaluation, security, observability, and delivery practices required to operate non-deterministic systems in a 24x7 environment: golden datasets and regression testing; tracing, failure-mode review, and production monitoring; prompt-injection defense, permission and data-boundary enforcement, and runtime guardrails; and cost and latency budgets with progressive rollout. Deliver enterprise full-stack solutions end to end, spanning C# / ASP.NET and C++ services, RESTful APIs, SQL data models, and Angular front ends on containerized Kubernetes platforms with CI/CD. Hold AI components to the same delivery and operatio

As a Staff Software Engineer on Coder’s Agentic Engineering team, you’ll shape the systems behind our agentic development experience. You’ll work across the agent harness, integrations, and workflows that connect agents with real development environments. You’ll stay hands-on while setting the team's technical direction. You’ll lead complex work, make sound architectural decisions, and help other engineers do their best work. What you’ll do here Set technical direction across Coder’s agent harness, integrations, and workflows. Design and build production systems in Go, with work across React and TypeScript where needed. Evolve agent execution, tool use, context management, streaming, and long-running workflows. Extend our provider-agnostic architecture as models and capabilities change. Lead complex projects from early ambiguity through production. Raise the engineering bar through design reviews, code reviews, and technical mentorship. Partner with Product and Design on clear, useful agent experiences. Improve the reliability, performance, and operability of agentic systems. What we’re looking for Deep experience building and operating production software systems. Strong hands-on experience with Go. Experience with React and TypeScript. Hands-on experience building systems around LLMs and agentic workflows. Experience with model APIs, tool calling, context management, or agent loops. Strong distributed systems knowledge. Working knowledge of AWS. A track record of setting technical direction without formal authority. Strong architectural judgment and comfort working through ambiguity. Someone who makes the engineers around them better. Our tech stack Backend: Go, Postgres Frontend: TypeScript, React Infrastructure: AWS, Kubernetes Observability: Prometheus, Grafana CI/CD: GitHub Actions Bonus tacos if you have (Tacos? If you need an ice-breaker, ask how we say thanks by giving tacos!) Experience building coding agents, developer tools, or cloud development environm