Staff Production Engineer Public Sector Jobs

Datadog’s Cloud Networks team designs, builds, and maintains the production network infrastructure that powers everything built on top of our platform across AWS, GCP, Azure, and beyond. In this role, you’ll set technical direction for how we scale our multi-region, multi-cloud network footprint while keeping reliability and performance high. You’ll partner closely with internal teams and Cloud Service Providers to troubleshoot complex connectivity issues, integrate new networking capabilities, and improve the foundations our engineers and customers rely on. This is a high-impact opportunity to drive meaningful improvements in scale, resiliency, and cost efficiency. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Design, build, and operate cloud network infrastructure across AWS, GCP, Azure, and Neoclouds in a multi-region environment. Own connectivity between clouds, customers, and developers—ensuring scalable, secure, and reliable network paths. Set clear technical direction for expanding data centers and evolving the network while maintaining stability and performance. Improve cross-site and cross-region connectivity patterns to support Datadog’s growing platform needs. Lead deep investigations into latency, packet loss, and connectivity failures – from pcap and path analysis through to escalations with cloud providers that may originate from customer support Identify and deliver network-related efficiency and cost-saving opportunities that positively impact business health. Who You Are: You have deep networking expertise. You understand BGP, route policies, path selection, prefix advertisement, and what breaks in large-scale networking. You have substantial experience designing, building, and evolving large-scale Software-Defined Networks—inclu

Staff Backend Engineer- Tech Lead |100% Remote | US- SaaS Fintech (Product based firm) Role Responsibilities: Design, develop, and maintain systems on the payments team with primary focus on backend Collaborate with cross-functional teams—product, and design Participate in sprint planning, feasibility assessments, and code reviews Write clean, maintainable, and testable code in Focus on scalability, security, performance, observability, auditability, testability and long-term maintainability Contribute to improving SDLC processes and engineering best practices Troubleshoot production issues and deliver timely resolutions What We're Looking For: 8-12 years of backend engineering experience with a high agency mindset Deep expertise in any of the backend languages (Go or Ruby preferred) Solid grasp of payments domain Proven experience working in Agile/Scrum environments Strong API development skills (RESTful architecture) Excellent problem-solving and communication abilities AI fluent Bonus Points For: (Good to have skills) Experience with payment gateway integrations Familiarity with PCI compliance and secure coding practices Skills in performance optimization (DB, code, etc.) Exposure to GCP or other cloud platforms

Opportunity Overview: This is a unique opportunity to join a high-caliber software engineering team that is growing quickly. You will play a key role in building impactful healthcare technology on a modern technology stack, with a focus on our core data and AI platforms. Your work will focus on enhancing the platform's key features, while also balancing scalability, reusability, and performance. Role Overview: We're looking for a Staff Platform Engineer to serve as the technical backbone of our Engineering organization. You'll own the technical strategy, and delivery of our platform — spanning architecture, DevOps, SRE, security, Dev-ex. This is a hands-on staff level role: you'll set technical direction, drive cross-team alignment, and be the senior escalation point for platform challenges. What you’ll do: Drive platform reliability, scalability, security, and cost efficiency across all environments. Technical Leadership: Provide technical leadership for platform components, Influence the technical strategy and architecture of our cloud platform, from CI/CD pipelines to observability and incident response. Design and implement platform components and reusable integration patterns that minimize custom development efforts, reduce the time spent on repetitive tasks, and ensure that integrations scale across multiple healthcare systems Partner closely with Architecture, DevOps, SRE, and Security teams to deliver cohesive platform solutions Cross-Functional Collaboration: Work closely with product teams, and solutions architects to understand integration needs and ensure the platform meets current and future business requirements. Serve as a senior escalation point for infrastructure and platform incidents Establish frameworks for: AI governance and compliance. Observability of systems. Traceability of decisions and outputs. Ensure enterprise readiness with security, auditability, and reliability in production environments. Security & Compliance : Ensure all p

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 and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Staff Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, ent

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. Engineering owns cost visibility and optimization across Affirm's cloud and AI infrastructure. We're the team that tells the business what it's spending, why it's changing, and what to do about it — from AWS resource waste and tagging strategy to the newer frontier of AI/LLM spend across the company's growing set of AI tools. We treat cost anomalies with the same rigor as production incidents: we've built a severity framework (mirroring Affirm's SEV0–3 incident model but mapped to dollar impact) with defined detection sources, TTD/TTR metrics, and escalation paths, and we operate a clear RACI with partner orgs — we own visibility and alerting, and partner teams own remediation (at times we may dig in deep and own remediation too!), so accountability never gets diffuse. As a Staff Cost Engineer, you'll operate at the intersection of finance, infrastructure, and data engineering — designing the tooling, automation, and processes that scale cost governance across a fast-growing multi-cloud and multi-AI-vendor footprint. You'll set technical direction for the team, influence cost strategy with infra and platform leaders across the org, and turn ambiguous "why did spend spike" questions into durable systems and self-service tooling. We're a small, high-leverage team — you'll have outsized influence on how Affirm thinks about cost. What You'll Do · You will be responsible for setting technical strategy for your team on a year-long time scale, and help your team tie it together with critical, business-impacting projects. · You will collaborate across teams in the product development lifecycle by collaborating with product management, design & analytics to ensure technical sustainability, risks and trade-offs are well understood and managed. · You will act as a force-multiplier for your team th

The Forward Deployed Engineer, Staff (FDE) is a high impact technical leader responsible for translating the immense power of Talkdesk's Agentic AI platform into transformative, production grade solutions for our strategic enterprise customers. You are a unique blend of a highly experienced software engineer, a technical project lead, and a hands-on builder. You own the technical execution for deployments, mitigate technical risks, and drive successful customer outcomes across assigned projects. This role is for the experienced builder who excels in high stakes, customer facing environments and is passionate about defining the future of Customer Experience Automation. Responsibilities Technical Project Leadership & Architecture: Act as the technical lead for complex deployments. Design and implement the architectural blueprint for AI agent solutions, manage cross-system dependencies, and ensure designs meet stringent enterprise standards for security and scale. Hands-On Engineering & Delivery: Write production-grade code and leverage Talkdesk and 3rd-party APIs/SDKs to design, build, test, and deploy AI agents. Drive the execution from prototype through to production deployment, ensuring technical quality. Technical Consultation & Alignment: Serve as a trusted technical expert for our AI solutions. Confidently address deep technical inquiries, mitigate technical risk, and build trust with customer Engineering Directors, and technical architects. Influence Product & Engineering Roadmap: Synthesize and codify deployment learnings into reusable solution patterns and tooling. Provide actionable feedback to core Product and Engineering teams to help inform future product direction. Technical Guidance: Mentor junior FDEs and technical specialists on best practices for complex AI architecture, production quality, and client-facing technical delivery. Who You Are We are looking for an autonomous, results-driven technical leader who thrives at the intersectio

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

Staff Software Engineer – Build Platform Location: Remote (U.S.) or Hybrid (Bay Area Preferred) Security Requirement: U.S. Citizenship is required due to the nature of RapidFort's work supporting U.S. Department of Defense (DoD) and other federal customer engagements. About RapidFort RapidFort is redefining software supply chain security. Modern enterprises spend enormous effort identifying software vulnerabilities. We believe the future isn't finding more vulnerabilities—it's eliminating them automatically. Our platform transforms vulnerable container images into production-ready, hardened artifacts that dramatically reduce software supply chain risk without requiring application code changes. By combining automated container hardening, vulnerability remediation, runtime intelligence, and policy automation, RapidFort enables engineering teams to deliver secure software faster while reducing operational complexity. We're solving some of the most challenging problems at the intersection of cybersecurity, Linux, distributed systems, containers, Kubernetes, and cloud infrastructure. If you're passionate about building platforms that power secure software at scale, you'll have an outsized impact here. The Opportunity RapidFort's platform is built on one simple idea: software should reach production already secure. Every day, our build platform transforms thousands of vulnerable open-source container images into hardened, production-ready artifacts that help enterprises and U.S. government agencies dramatically reduce software supply chain risk. We are looking for a Staff Software Engineer – Build Platform to architect, scale, and evolve the systems that make this possible. This is not a traditional DevOps or CI/CD role. This is a senior technical leadership position where you'll own one of the most critical engineering platforms at RapidFort. You'll define the architecture behind our distributed build systems, influence engineering direction across multiple teams, and b

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's Environments organization builds and maintains the infrastructure that improves Claude’s capabilities through reinforcement learning. That includes the frameworks researchers use to build environments and the infrastructure responsible for running them. The team's mission is to productionize research. You'll embed with research teams, get up to speed on how they work, and design the frameworks and APIs that let them move faster, building systems the team can understand, own, and maintain themselves. Scope also includes keeping production RL runs healthy, maintainable, monitored, and easy to triage. You'll be a strong fit if you have deep expertise in Python, a refined sense of taste for API and framework design, and good intuition for how complex systems fail, especially silently. It's a bonus if you've built and operated a stateful distributed system, such as a workflow engine, actor framework, or durable-execution runtime, where correctness depends on getting shared state and recovery right. You should be comfortable diving into messy research code, finding the abstractions that matter, and improving them incrementally while researchers continue to build on your work. You should also be comfortable using AI tools to accelerate your own development, but have an impulse towards deep verification. Key responsibilities Design widely used APIs, frameworks, and abstractions that other engineers and researchers build on, making correct usage the default and ruling out entire classes of errors structurally Own the platform layers that sit beneath every environment, including the agent runtime Build the

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 GTM Systems builds and runs the platform that Sales and contracting operate on. These are production systems that process real transactions and produce the data the rest of the company depends on, and the team has grown into a scope where the engineering practices need to grow with it. The platform-developer model got us here. The next stage is a team that operates as software engineers on top of it. We are hiring a technical lead to build that next stage. You will design and stand up the engineering motions the team runs on, from pull requests and CI/CD through automated UAT, and you will set the technical bar by working alongside the team rather than legislating from the side. Anthropic is also an unusual place to do this work: our own frontier models are part of your toolkit, the team already uses them daily, and a real part of this role is turning that individual usage into a coordinated engineering practice. Key responsibilities Lead architecture reviews for GTM systems that process lead-to-cash transactions and generate the data points the organization runs on, including changes originating in other teams that land on our platform Architect and mature the engineering pipeline the team develops against: pull request workflow, CI/CD, automated UAT, and the deploy path from source control to production Establish shared AI-assisted development standards for the team, converting existing individual usage into consistent practice that holds up under review Work with engineering teams outside GTM on shared architectural problems and common tooling, where the right answer is a platform decision rather than a local one Bui

P-1691 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 Software Engineer 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 Observability: Impl

About the job Build the test solutions that help bring advanced AI hardware from design into volume production. As a Staff Board Test Operations Engineer, you'll develop and deploy PCB assembly test solutions across our manufacturing network. Your work will help ensure product quality, reliability, and manufacturing readiness. You'll play a key role in identifying defects early, improving test coverage, and resolving complex production challenges. The impact of your work will be seen in yield performance, efficiency, and product quality. You'll lead the development of flying probe and ICT test solutions, support external manufacturing partners, and drive test platform deployment from NPI through to mass production. This role offers broad technical scope across design, manufacturing, test engineering, and operations. You'll solve difficult problems and help shape how our products are tested at scale. The team and culture The Product Test and Diagnosis team focuses on finding and managing hardware defects across chips, boards, and complete systems. The work spans manufacturing sites and products in the field. Day to day, you'll work closely with design engineers, manufacturing teams, and external test partners. Problems are solved through data, root cause analysis, and hands-on engineering. Ownership sits with the people closest to the challenge. Team members are trusted to lead technical decisions, improve processes, and raise standards across the organisation. What we’re looking for Strong experience developing and maintaining PCB assembly test solutions using platforms such as Teradyne, Keysight, TRI, or SPEA Deep understanding of SMT and PCB manufacturing processes, failure mechanisms, and test coverage principles Ability to debug complex issues across design, test, and manufacturing environments Experience working with manufacturing partners and supporting production test operations Hands-on experience with electronic test equipment, including oscilloscopes, DMMs

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

About the Role: We are looking for a Staff Engineer to steer the technical evolution of our AI-centric business platforms, which currently prioritize ad revenue operations such as cross-system intelligence, workflow automation, and document understanding. While the domain already supports live production traffic and active users, significant architectural challenges remain: how can non-deterministic AI be effectively integrated into workflows where business outcomes depend on high accuracy? Furthermore, how should system boundaries be structured during this phase of rapid platform integration and development? In this role, you will confront this ambiguity head-on—defining architectural patterns, implementing them in production, and validating their effectiveness. About the Team: Tubi’s Internal Tools team is at the forefront of AI integration, developing everything from developer resources to production-grade AI for business operations. We are the group responsible for turning AI from an experiment into an operating capability: training, infrastructure, developer agents, and AI-powered business systems. Engineers operate with high ownership and autonomy, collaborating on shared architectural decisions and AI infrastructure. What You'll Do: Define and drive the technical architecture of the AI platform — spanning extraction pipelines, confidence scoring, cross-system data aggregation, and user-facing intelligence layers. Ensure systems are modular, testable, and evolvable. Own the platform's most complex subsystems and hardest design problems: reliability under non-determinism, integration across heterogeneous data sources, and progressive automation with appropriate human-in-loop gates. Establish clear system boundaries and integration contracts with adjacent platforms. Design interfaces that are resilient to schema evolution and organizational change. Ship consistently. Turn ambiguous requirements into working software that users see and trust. Bias toward iteratio

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