Production Operator Jobs

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 . The CX Intelligence Engineering team, part of Coinbase's Enterprise Applications and Architecture org, builds the multi-agent platform powering Coinbase Chat, Help Center, and agent tooling. As a Machine Learning Engineer on this team, you'll design and scale the agentic systems that automate complex customer support workflows, connecting LLMs with internal APIs and tools to deliver fast, accurate, and compliant AI-powered experiences for millions of customers. What you'll do: Architect multi-agent systems using advanced orchestration frameworks (LangGraph, Google ADK) to automate complex customer support procedures end-to-end. Build and scale integrations using Model Context Protocol (MCP) to connect LLMs with internal Coinbase APIs, databases, and third-party tooling. Develop automated "LLM-as-a-judge" evaluation pipelines to monitor, measure, and improve the performance of non-deterministic AI agents in production. Implement RAG, fine-tuning, and prompt engineering techniques to ensure chatbot responses are grounded, accurate, and compliant with Coinbase policies. Ship production-ready Python services that are resilient, low-latency, and capable of handling Coinbase-scale traffic across asynchronous microservices. Partner with Conversation Design and Product to translate complex business logic into executable agent procedures within the decentralized architecture.

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 . As a Solutions Architect on the Sales, Trading and Prime team, you'll help scale our B2B products by bridging technical field engagement with hands-on software development. You'll work directly with customers, from startups to large institutions, as a trusted technical advisor while contributing to open source projects and extending Coinbase's core products to unlock strategic client opportunities. This role involves substantial coding, and candidates must be actively developing and delivering software in their current role. What you’ll do: Partner with customers as a trusted technical advisor, guiding them in building on Coinbase services and APIs and deepening relationships as they scale. Collaborate with sales teams to address prospect technical requirements and support deal closure. Architect distributed systems solutions for complex customer needs and build open source SDKs and reference implementations. Lead customer implementations end-to-end, delivering technical presentations, resolving roadblocks, and partnering with support teams to ensure success. Drive collaboration with product and engineering teams to extend core capabilities for strategic client opportunities. Required skills and experience: Degree in computer science and 3+ years of software engineering experience, including expert-level proficiency with REST and WebSocket APIs and production experie

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 . Senior Software Engineer, Backend - Platform (Tokens & Wrapped Assets) We're hiring a Senior Software Engineer to join the Tokens & Wrapped Assets team within the Platform organization. This team builds and operates the platform that issues, wraps, and transforms every asset at Coinbase, including flagship wrapped assets like cbBTC, spanning Ethereum, Base, and Solana. You'll own complex projects end-to-end, from smart contract through APIs and production rollout, designing and operating the Go services that mint, burn, bridge, and reconcile wrapped assets across chains. What you'll do: Own end-to-end delivery of complex token and wrapped asset initiatives, from smart contract deployment through API design, SLOs, and production rollout across multiple chains. Build and operate the Go services and smart contracts that mint, burn, bridge, and reconcile wrapped assets, ensuring correctness across on-chain and off-chain systems. Drive improvements to the asset transformation and migration pipeline, making it dramatically faster and safer to launch, upgrade, and migrate tokens at scale. Partner across Trading, Custody, USDC, Compliance, and the broader crypto stack to ship customer- and revenue-impacting work that advances onchain innovation. Lead on-call ownership for team services, building observability, runbooks, and operational improvements that keep T

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 . As a Senior Software Engineer on the Stablecoin team within the Developer group, you'll help build and scale Coinbase Custom Stablecoins (CCS), the platform that lets partners launch their own branded, USDC-backed stablecoins on Coinbase's infrastructure. This role sits at the intersection of backend engineering and smart contract development - you'll own the services and onchain contracts that power issuance, reserves, minting and burning, and rewards distribution for a fast-growing roster of partners. What you'll do: Own and evolve the smart contracts that mint, burn, and safeguard custom stablecoin supply, shipping changes in a secure and auditable way. Build and scale backend services that power onboarding, issuance, reserve accounting, and rewards distribution. Partner with product, design, and tech leads to turn the stablecoin roadmap into shipped features every quarter. Drive architectural decisions across the backend and smart contract surface, balancing security, scalability, and speed of delivery. Write high-quality, well-tested code and raise the bar for operational excellence across the team. Required Skills and Experience: 5+ years of experience in software engineering, including designing, building, and operating production backend services. Experience writing, testing, and deploying smart contracts (Solidity or similar EVM languages) in production, ide

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Our Applied ML team aims to reform how our users interact with Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include helping our users resolve issues with Stripe faster or making it easier for our users to sign up and navigate Stripe. We are using the latest LLMs as well as fine-tuning our own models. We're an end-to-end team going from ideas to models to shipping in production. You can learn more about our team’s work from this recent talk . What you’ll do As a machine learning engineer, you will be responsible for analyzing opportunities, proposing ideas, training & evaluating ML models, running experiments, and deploying everything to production. You will also have the opportunity to contribute to and influence ML architecture at Stripe as well as be a part of a larger ML community. Responsibilities Our team operates fluidly and here are some problems you may tackle: How do we evaluate a system offline & online? How do we improve performance to match (and beat) humans? How do we ensure model quality doesn’t degrade online? Does fine-tuning an LLM give us better performance? What are the right OSS and in-house platforms we should invest in? And in the process you will: Develop pipelines and automated processes to train and evaluate models in offline and online environments Integrate ML models into production systems and ensure their scalability and reliab

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! This is a hybrid role that will require two days in-office each week on Tuesdays and Wednesdays at our SF location on 130 Sutter Street. About the Role Every business function at Taskrabbit — Marketing, Customer Support, Finance, Operations — is a "customer" with real workflows, real data, and real friction. Your job is to embed with them, scope their use cases, and build the Claude-powered agent, automation, or tool that solves them. This is an internal-facing role — there is no external customer or product work. Reporting to the Director of AI Strategy and Enablement, you'll operate the way an FDE operates at a high-growth AI company: full ownership of a deployment from discovery through production and direct accountability for whether what you ship actually changes a metric. In most cases you'll own a build end-to-end solo; in some functions you may partner with that team's own subject-matter expert to pair domain depth with

About the Team The Ecosystem AI Deployment Engineering (ADE) team supports strategic partners as they build high-quality technical integrations into ChatGPT and Codex. Our goal is to create products users depend on, drive adoption and retention, and build an ecosystem where partners win when OpenAI wins. About the Role We are looking for an AI Deployment Engineer to help strategic partners design, build, evaluate, submit, launch, and maintain high-utility plugins for ChatGPT and Codex. This is a hands-on, partner-facing product engineering role for someone who can contribute to the platform itself, lead sophisticated partner engagements, and translate ambiguous product needs into production-ready integrations. You will work across partner product and engineering teams and OpenAI's product, engineering, partnerships, legal, policy, design, and go-to-market teams. You will identify the right use cases, prototype and review implementations, run evaluations, debug issues across systems, guide partners through submission and review, and support launch and post-launch iteration. The best person for this role moves fluidly between code, product judgment, project leadership, and clear communication with engineers and executives. This role is a fit for a product minded engineer who wants to stay close to users and partners while still going deep on code, reliability, evaluations, and developer experience. The goal is to help partners ship plugins that are not merely technically functional, but genuinely useful in ChatGPT and Codex. This role is based in our San Francisco office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own the technical partner journey for priority B2B plugins—from pitch and readiness assessment through architecture, build, evaluation, submission, launch, and ongoing maintenance. Identify strong plugin use cases, define crisp user journeys and expected behaviors, and

About the Team OpenAI’s Infrastructure Operations team is responsible for the availability, reliability, and operational excellence of one of the world’s largest AI infrastructure networks. The team owns day-to-day operations of production AI networks across Industrial Compute's data centers, working with colocation providers, deployment teams, and hardware vendors to deliver highly available GPU infrastructure for AI training and inference workloads. About the Role We are seeking an Infrastructure Operations Engineer to operate and improve the large-scale Ethernet fabrics that support GPU clusters, storage systems, and management infrastructure. This role combines hands-on production operations with automation, observability, and incident response across a global AI network. The ideal candidate has experience operating high-availability data center, cloud, AI, or HPC networks and can move comfortably from physical-layer troubleshooting to routing and fabric behavior, change execution, and root-cause analysis. You will partner closely with network architecture, systems engineering, GPU engineering, storage engineering, security, deployment, site operations, service providers, colocation partners, and hardware vendors to raise reliability and reduce operational toil. Key Responsibilities Own the operational health, availability, and reliability of production AI network infrastructure across Industrial Compute's data centers. Monitor, troubleshoot, and resolve network incidents while meeting service-level objectives (SLOs), reducing Mean Time to Detect (MTTD), and minimizing Mean Time to Recovery (MTTR). Operate and maintain large-scale Ethernet fabrics supporting GPU compute, storage, and management networks. Execute production network changes, maintenance windows, and capacity expansions with minimal customer impact. Manage the hardware lifecycle, including switch and optics replacements, RMA coordination, software upgrades, and preventive maintenance. Support new A

About the Team Data Platform at OpenAI owns the foundational data stack powering critical product, research, and analytics workflows. We operate some of the largest Spark compute fleets in production; design, and build data lakes and metadata systems on Iceberg and Delta with a vision toward exabyte-scale architecture; run high throughput streaming platforms on Kafka and Flink; provide orchestration with Airflow; and support ML feature engineering tooling such as Chronon. Our mission is to deliver reliable, secure, and efficient data access at scale and accelerate intelligent, AI assisted data workflows. Join us to build and operate these core platforms that underpin OpenAI products, research, and analytics. We’re not just scaling infrastructure – we’re redefining how people interact with data. Our vision includes intelligent interfaces and AI-assisted workflows that make working with data faster, more reliable, and more intuitive. About the Role This role focuses on building and operating data infrastructure that supports massive compute fleets and storage systems, designed for high performance and scalability. You’ll help design, build, and operate the next generation of data infrastructure at OpenAI. You will scale and harden big data compute and storage platforms, build and support high-throughput streaming systems, build and operate low latency data ingestions, enable secure and governed data access for ML and analytics, and design for reliability and performance at extreme scale. You will take full lifecycle ownership: architecture, implementation, production operations, and on-call participation. You’ve supported Spark, Kafka, Flink, Airflow, Trino, or Iceberg as platforms. You’re well-versed in infrastructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure problems in the AI space. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per wee

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. We work with customer executives, product and engineeriIng teams, security leaders, and transformation teams to identify valuable opportunities, accelerate technical implementation, and scale what works. Enterprise deployments are defined by complexity rather than any one industry: existing architectures, diverse data environments, security and governance requirements, multiple stakeholder groups, and organization-wide change. We turn lessons from these deployments into better products and reusable patterns for customers everywhere. About the Role As an Enterprise Applied AI Engineer you will partner directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact—not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. This role is based in our SF or NYC office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteri

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. We work with customer executives, product and engineering teams, security leaders, and transformation teams to identify valuable opportunities, accelerate technical implementation, and scale what works. Enterprise deployments are defined by complexity rather than any one industry: existing architectures, diverse data environments, security and governance requirements, multiple stakeholder groups, and organization-wide change. We turn lessons from these deployments into better products and reusable patterns for customers everywhere. About the Role As an Enterprise Applied AI Engineer, you will partner directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact—not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. In this role, you will: Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria. Design, build, and deploy AI systems that solve important customer problems and produce measurable business outcomes. Work hands-on in code to build pr

About the team The AI Deployment Engineering team ensures the safe and effective deployment of Generative AI applications for developers and enterprises. We serve as trusted technical advisors, helping customers and partners move from early experimentation to production-scale AI systems. As a Partner AI Deployment Engineer focused on AWS, you will operate at the center of one of our most strategic partnerships, driving joint customer success and enabling AWS and partner ecosystems to scale adoption of OpenAI-powered solutions. About the role We are looking for a highly experienced technical leader to serve as the primary technical counterpart to AWS field leadership (Solutions Architects, Specialists, and Partner teams). This role goes beyond individual deal support—you will shape strategy, define engagement models, and build repeatable systems that scale across AWS globally. You will work across pre- and post-sales, guiding complex enterprise customers from ideation to production while enabling AWS and partners to independently drive deployments. You will combine deep technical expertise, strong judgment, and ecosystem leadership to maximize impact across a portfolio of high-priority opportunities. This role is based in Bangalore . In this role, you will: Strategic AWS Engagement & Influence Serve as the senior technical counterpart to AWS field leadership, building trust and credibility across regions and teams. Influence joint account strategy and technical direction for high-priority opportunities. Shape how OpenAI engages with AWS by defining engagement models, prioritization frameworks, and best practices. Proactively identify and drive net-new opportunities and high-impact use cases across the AWS ecosystem. Complex Deal Leadership & Execution Lead technical strategy for large, ambiguous, and high-stakes enterprise engagements. Guide customers from early ideation through architecture design, prototyping, and production deployment. Act as a technical d

About the team The Applied AI Engineering (AAE) team is responsible for helping developers and enterprises turn the potential of generative AI into real-world impact. We act as trusted advisors and technical partners to customers and ecosystem partners, helping identify high-impact AI use cases and bring them into production through strong architectural guidance and hands-on execution. The Partner Applied AI Engineering organization works closely with strategic cloud providers, systems integrators, consultancies, and implementation partners to scale successful adoption of OpenAI technologies. As the leader of the AWS Partner AAE pod, you will manage a team of Applied AI Engineers focused on enabling AWS-aligned partners and their customers to build, deploy, and operationalize AI applications on OpenAI’s platform. About the role We are seeking a Manager, Partner Applied AI Engineering – AWS to lead a team of Applied AI Engineers supporting strategic AWS ecosystem partnerships. In this role, you will own the technical success strategy for AWS-aligned partners and help build scalable, repeatable ways for partners and their customers to adopt OpenAI technologies. Your team will guide partners and customers across the full AI implementation lifecycle—from identifying and shaping high-value use cases to solution design, architecture, production deployment, optimization, and adoption growth. You will work cross-functionally with internal and external stakeholders across Sales, Partnerships, Product, Research, and Engineering to ensure the voice of partners and customers informs our platform roadmap and how we bring OpenAI technology into production at scale. This role requires a blend of technical depth, customer leadership, operational rigor, and people management. Success will be measured through production deployments, partner technical maturity, API adoption growth, team development, and the overall impact of the AWS partner ecosystem. This role is based in our San Fra

About the Team The Storage Infrastructure team builds and operates the storage foundation behind OpenAI’s most demanding workloads. We work directly with research to design storage systems for rapidly evolving experiments, while also powering production at scale. We own the platform end to end: backend systems, user-facing services and APIs, and the control planes that manage how data is placed, moved, and retained over time. Our stack spans cloud and in-house object stores across very different workload profiles, from GPU-attached systems to dedicated storage hardware. We also build the federation layer that unifies these backends behind a simple interface and routes each workload to the right storage solution. About the Role You will help build the storage platform that powers OpenAI’s research and production systems. This is a hands-on infrastructure role for engineers who want to work on deeply technical systems at scale and own them in production. You’ll work across object storage, cross-region data movement, lifecycle management, and the federation layer that provides a unified interface across multiple backends. Much of our stack runs on Kubernetes, and we primarily build services in Rust. In this role, you will: Build and operate storage services that underpin OpenAI’s research infrastructure Develop object storage systems across cloud and in-house environments Build systems for cross-region data movement, replication, and recovery Design lifecycle management capabilities that keep data durable, available, and cost-effective Evolve the federation layer that unifies multiple backend systems behind a simple interface Improve performance, reliability, and operational excellence across the platform Collaborate closely with researchers and infrastructure teams to support rapidly evolving workloads You might thrive in this role if you: Have experience building or operating distributed systems in production Have worked on storage infrastructure, object stores, dist

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. We work with customer executives, product and engineering teams, security leaders, and transformation teams to identify valuable opportunities, accelerate technical implementation, and scale what works. Enterprise deployments are defined by complexity rather than any one industry: existing architectures, diverse data environments, security and governance requirements, multiple stakeholder groups, and organization-wide change. We turn lessons from these deployments into better products and reusable patterns for customers everywhere. About the Role As an Applied AI Engineer you will partner directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact—not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. This role can be based in Delhi, Mumbai or Bangalore. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees In this role, you will: Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria.