Staff Production Engineer Public Sector Jobs

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability. You will: Own large new areas within our product Work across backend, frontend, and interacting with LLMs and ML models Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly Ideally you'd have: 7+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval

RDQ226R605 This role can be based remotely anywhere in the United States. About Databricks Databricks is the data and AI company. More than 12,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. About the Team The Agentic Security Engineering team is a horizontal, shared services engineering team that makes every Databricks security function AI-native — building the AI agents, "personas," and shared platform that security teams across the org (Detection & Response, Threat Intelligence, Vulnerability & Product Security, Red Team, GRC, and Continuous Monitoring) build on to operate at machine speed, safely and reliably. We leverage AI to transform how security is done. The Role As Staff Security Software Engineer , you own a major technical workstream designing and shipping production-grade AI agents and the platform capabilities that power them, with reliability, observability, and safe-by-default security as first-class requirements. You set the standards for how agents are built and operated and co-build with partner security teams. Example use cases you'll enable, led by AI threat detection at scale (alert triage and false-positive reduction, fleet-scale anomaly detection), extend to threat hunting, vulnerability management, product security, red team/offensive testing, and GRC/assurance use cases. The Impact You Will Have Agentic Security Engineering Architecture Design, ship, and operate production AI agents/personas that security teams depend on, starting with AI threat detection at scale. Build and harden the shared platform so any security team can ship agents safely and reliably — i.e., sandboxing, scoped least-privilege identity, obs

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 build the data systems that help teams understand and manage infrastructure usage and cost. You’ll lead the design and hands-on delivery of reliable data products, including pipelines, models, and services, that support infrastructure planning, cost attribution, and budget workflows. In this individual-contributor role, you’ll shape technical direction, navigate complex cross-team work, and make infrastructure data more accurate, consistent, and useful. What you’ll do: Set technical direction and help define a roadmap for reliable, scalable infrastructure data products Design, build, and operate production ingestion and transformation pipelines, data models, and services for infrastructure usage, cost, ownership, and planning Strengthen shared data products with clear contracts, automated quality

About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Product Engineering at Decagon builds all aspects of the platform our customers use to create, operate, and improve their AI agents. We turn work that currently requires an engineer into product that a CX team can run themselves. This team is core to how Decagon scales. The frameworks we build support every agent we have in production, each with its own workflows, data, and constraints. We build the agents too, and that’s what keeps the platform honest: a failure mode we debug in production becomes a guardrail, an eval, or a piece of tooling that catches it everywhere. Our agents run for companies like Hertz, American Airlines, and Notion across chat, voice, email, and SMS. About the Role You’ll design and build the systems that let customers configure, train, test, and monitor sophisticated AI agents with confidence. That means strong engineering underneath, and abstractions on top that hold up across different use cases without forking per customer. You’ll work day to day with prod

About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Product Engineering at Decagon builds all aspects of the platform our customers use to create, operate, and improve their AI agents. We turn work that currently requires an engineer into product that a CX team can run themselves. This team is core to how Decagon scales. The frameworks we build support every agent we have in production, each with its own workflows, data, and constraints. We build the agents too, and that’s what keeps the platform honest: a failure mode we debug in production becomes a guardrail, an eval, or a piece of tooling that catches it everywhere. Our agents run for companies like Hertz, American Airlines, and Notion across chat, voice, email, and SMS. About the Role You’ll design and build the systems that let customers configure, train, test, and monitor sophisticated AI agents with confidence. That means strong engineering underneath, and abstractions on top that hold up across different use cases without forking per customer. You’ll work day to day with prod

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the Role Sentry helps developers identify and resolve issues in their applications. Behind our products is a complex foundation of distributed systems, cloud infrastructure, and services that must perform reliably at scale. Our Platform and Infrastructure Engineering teams build and operate the systems that power Sentry. From cloud infrastructure, distributed storage, and real-time event processing to service reliability, scalability, and developer productivity, these teams provide the technical foundation that enables our products and engineering organization to grow. We're looking for Staff Software Engineers to tackle some of Sentry's most challenging infrastructure and distributed systems problems. Depending on your experience and interests, you might work on scaling our real-time event processing systems, improving the reliability and efficiency of our cloud infrastructure, or designing and building foundational services that support our products. In this role, you'll have the autonomy to identify important technical problems, lead solutions from design through production, and influence engineering decisions beyond your immediate team. We're looking for engineers who enjoy solving difficult problems, remain hands-on with the systems they build, and take pride in delivering meaningful technical impact. In This Role, You Will Design, build, and operate reliable, scalable distributed systems that support Sentry's products and engineering teams. Own technically complex projects from identifying problems and defining solutions through implementation, deployment, and production operations. Solve challenging engineering

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. Staff Data Engineer, Enterprise Core Datasets, Tech Foundations The Community You Will Join: At Airbnb, trustworthy data powers business decisions, product innovation, and operational efficiency. The Enterprise Core Datasets team builds the technical data foundations that help Airbnb understand how the business operates, where resources are invested, and how new technologies create value. Our scope spans high-impact datasets across the organization: measuring AI adoption, usage, and cost; understanding revenue, costs, and profitability through Unit Economics; integrating non-platform data from Jira and other enterprise applications; and powering critical company metrics such as Gross Booking Value and Revenue. You will join a team that values thoughtful architecture, engineering rigor, and operational ownership. We collaborate with engineering, product, analytics, finance, and business teams to turn complex requirements into dependable, reusable data assets. We welcome strong engineers who are curious about the business and eager to solve problems across diverse domains. The Difference You Will Make: As a Staff Data Engineer, you will provide hands-on technical leadership for datasets that shape decisions across Airbnb. Your work will help the organization measure AI adoption and spending, understand the economics of its products, and connect enterprise application data to meaningful business and operational insights. You will lead complex initiatives from problem definition and architectural design through implementation, validation, and production operations. You will build extensible data foundations that ac

About the role Chime's Data Science & Machine Learning team builds the models, services, and platforms behind how millions of members manage and grow their financial lives. We're hiring a Staff AI/ML Engineer on our Lending and Cashflow team to lead the modeling behind cash flow underwriting and surface member insight: using members' transaction and deposit data to make fair, accurate credit decisions for people that traditional credit scores often miss. In this role, you'll build and deploy machine learning systems on some of the richest transactional and behavioral data in fintech, turning it into the credit decisions behind products like MyPay, Instant Loans, and SpotMe. This is a highly applied role: you'll own problems end to end, from framing the question through to a model running in production and moving a metric that matters, and you'll set the technical direction for how Chime underwrites with cash flow data. In this role, you can expect to Lead the design, training, and deployment of deep learning and classical ML underwriting models that turn members' transaction and cash flow data into credit decisions, from approval and line assignment to loss forecasting Take models from problem framing through to production — training, evaluation, deployment, monitoring, and iteration — and stay accountable for how they behave once they're live Design and improve the systems around the model: feature pipelines, batch and real-time inference, monitoring, and retraining Partner with Product, Engineering, Analytics, and Risk to turn ambiguous business problems into ML solutions, and to make sure the solution is the right one Connect model performance to member outcomes and business metrics, and use experimentation to prove impact Set the technical roadmap for Lending ML and raise the bar across the team through design reviews, mentorship, and shared standards for model development, validation, and governance Help identify where AI/ML creates measurable impact for me

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,500 firms in 60 countries use Addepar to manage and advise on nearly $10 trillion in assets. Its open platform integrates with 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and levels of complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, São Paulo, London, Edinburgh, Geneva, Warsaw, Dubai, Pune and Singapore. The Role The Applied AI team works embedded with Addepar's strategic clients to figure out where AI can change how they work and then build those capabilities from scratch. You'll spend time understanding a client's world, identify what's worth building, prototype it, prove it works, and then partner with core engineering teams to ship it as product for all customers. As an Applied AI Engineer, you'll build agentic systems from idea through production. The work starts with understanding the problem well enough to know what to build, then moves fast through prototyping and iteration. You'll design agent behavior, wire up tool integrations, tune evaluations until the AI actually works in practice. You'll sit close to the people who use what you build, and that feedback loop is how both the product and your skills grow fast. The team is new. Your work shapes what we ship. This role may require occasional work outside standard business hours to accommodate client time zones and up to 15% travel to client sites, including occasional overnight and multi-day engagements. What You'll Do Build AI-powered agents and tools end-to-end: identify the problem with clients and domain experts, prototype quickly, evaluate rigorously, and ship to production Desig

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,500 firms in 60 countries use Addepar to manage and advise on nearly $10 trillion in assets. Its open platform integrates with 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and levels of complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, São Paulo, London, Edinburgh, Geneva, Warsaw, Dubai, Pune and Singapore. The Role The Applied AI team works embedded with Addepar's strategic clients to figure out where AI can change how they work and then build those capabilities from scratch. You'll spend time understanding a client's world, identify what's worth building, prototype it, prove it works, and then partner with core engineering teams to ship it as product for all customers. As an Applied AI Engineer, you'll build agentic systems from idea through production. The work starts with understanding the problem well enough to know what to build, then moves fast through prototyping and iteration. You'll design agent behavior, wire up tool integrations, tune evaluations until the AI actually works in practice. You'll sit close to the people who use what you build, and that feedback loop is how both the product and your skills grow fast. The team is new. Your work shapes what we ship. This role may require occasional work outside standard business hours to accommodate client time zones and up to 15% travel to client sites, including occasional overnight and multi-day engagements. What You'll Do Build AI-powered agents and tools end-to-end: identify the problem with clients and domain experts, prototype quickly, evaluate rigorously, and ship to production Desig

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary The Staff CDN Engineer is a highly experienced, hands-on technical leader responsible for enterprise content delivery, edge computing, web performance, DNS, traffic management, and application security solutions. This role defines architecture and engineering standards, builds reusable automation and self-service capabilities, and partners across application, infrastructure, cloud, network, and security teams. The engineer also provides operational ownership by participating in on-call support, leading response to critical production incidents, supporting business-critical releases, and driving root-cause remediation and long-term service improvements. Through direct engineering contribution, technical influence, and mentorship, this role advances platform reliability, performance, security, scalability, and operational readiness. Roles and Responsibilities / Job Duties Define and evolve enterprise CDN and edge-delivery architectures, engineering standards, and reusable design patterns; build APIs, Infrastructure as Code modules, GitOps workflows, CI/CD pipelines, and self-service capabilities that standardize onboarding, deployment, configuration, validation, governance, and lifecycle management while reducing operational risk and recurring manual effort. Serve as the enterprise subject matter expert for CDN(Akamai), edge delivery,

About the Team DoorDash is building the world's most reliable on-demand, logistics engine for delivery. We are continuing to grow rapidly and expanding our Engineering offices globally! We are looking for Software Engineers, Machine Learning to build and maintain a large scale 24x7 global infrastructure system that powers DoorDash's 3-sided marketplace of Consumers, Merchants and Dashers. About the Role As a Software Engineer, Machine Learning, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the catalog system and our product knowledge graph at the heart of our fast-growing grocery and retail delivery business. You will use our robust data and machine learning infrastructure to implement new ML solutions to make our product knowledge graph accurate, standardized, semantically rich, easily discoverable, and extensible. We’re looking for someone with a command of production-level machine learning and experience with solving end-user problems who enjoys collaborating with multi-disciplinary teams. This role is hybrid with some in-office time expected and will report to an Engineering Manager. You're excited about this opportunity because you will... Develop advanced machine learning models to improve ads efficiency and quality. Design and build optimization algorithms for budget pacing and automated bidding to achieve various advertising goals. Establish a data-driven framework to understand how the bid density and market competitiveness would affect advertising value and platform revenue. Develop new data solutions (eg. embeddings and consumer profiles) to target the relevant audience. Be responsible for the end-to-end ML lifecycle, including ideation, offline model training, online shadowing/deployment, experimentation, and post-launch monitoring/measurement. Build and extend the current data/ML infrastructure to empower Ads data applications including data analysis, ML modeling, and experimentati

About the Team Come help us build the world's most reliable on-demand, logistics engine for last-mile retail delivery! We're looking for an experienced machine learning engineer to help us develop modern growth and personalization models that power DoorDash's growing retail and grocery business. About the Role We’re looking for a passionate Applied Machine Learning expert to join our team. As a Staff Machine Learning Engineer, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the growth and personalization experiences at the heart of our fast-growing grocery and retail delivery business. You will use our robust data and machine learning infrastructure to implement new ML solutions to make the consumer search experience more relevant, seamless, and delightful across grocery, convenience, and many other retail categories. You will demonstrate a strong command of production level machine learning, experience with solving end-user problems, and collaborate well with multi-disciplinary teams. You will report into the engineering manager on our Personalization team. We expect this role to be hybrid with some time in-office and some time remote (#LI-Hybrid). You’re excited about this opportunity because you will… Develop production machine learning solutions to build a world class personalized shopping experience for a diverse and expanding retail space Partner with engineering and product leaders to help shape the product roadmap applying ML Mentor junior team members, and lead cross functional pods to create collective impact You can find out more on our ML blog here We’re excited about you because you have… 8+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production. Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring an

Why RoboForce RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability. We are seeking a highly motivated Manufacturing Engineer to define and optimize manufacturing processes, develop production equipment, and provide manufacturing input during product definition for our advanced robotic systems. You will work closely with design, supply chain, and operations teams to establish reliable processes and equipment that meet quality, cost, and delivery requirements. Responsibilities Bridge the gap between initial concept and full production by providing design teams with critical insights on manufacturability, assembly, testing, and tooling. Apply design for manufacturing and assembly (DFM/DFA) principles and resolve manufacturability issues before production release. Define assembly sequences, work instructions, and tooling requirements; establish critical process and quality parameters; and validate processes before production release. Lead manufacturing readiness for new product launches, upgrades, and component changes by coordinating cost targets, resources, and schedules. Provide hands-on technical support and collaborate with external integrators and suppliers during tooling and equipment specification, validation, commissioning, and production ramp-up. Incorporate requirements for safety, product quality, resource utilization, and preventive maintenance into process and equipment design. Collaborate with cross-functional teams to synchronize priorities. Investigate manufacturing defects and process failures, implement corrective actions, and track improvements in yield, cycle time, and cost. Assess the manufacturing impact of engineering changes, update process documentation and tooling, and track risk mitigation actions through implementation. Requirements Bachelor’s degr

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. Department Intro: The Advanced Packaging Technology Development (APTD) team at Micron leads the creation of powerful memory and storage solutions that power the AI era. We work hands-on with global R&D groups, suppliers, and manufacturing teams to turn breakthrough ideas into real, production-ready technologies. We thrive on innovation and collaboration! Position Overview: This role will be part of a highly collaborative and innovative Advanced Packaging Wafer Edge Trim, Backgrind & Thinning R&D team, responsible for developing and scaling critical mechanical wafer processing modules. This role offers broad opportunities for technical innovation, early stage pathfinding, and ownership of process solutions that enable next generation advanced packaging technologies. You will work closely with process integration and adjacent process areas including Bonding/De-bonding, CMP, Wet Etch, Lithography, Assembly, and Test, while driving process readiness to meet bold program, performance, and yield targets. Responsibilities: Develop and optimize wafer edge trim, backgrind, and thinning processes to meet the mechanical, electrical, and reliability requirements of Micron’s advanced memory products. Improve process capability, yield, cost efficiency, and wafer integrity through data‑driven optimization and equipment or consumable innovation. Conduct root‑cause and failure‑mode analyses to understand wafer damage mechanisms such as edge chipping, micro‑cracks, subsurface damage,