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Ai Agent Engineer Jobs

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Explore current ai agent engineer jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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1mo ago

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we're searching for talented and motivated Principal Software Engineers with expertise in Identity and Access management who are passionate about continuous learning and eager to grow along with us in a fast-paced, innovative environment. You Will Lead the design and implementation of Smartsheet's next-generation architecture, ensuring scalability, security, and performance for millions of global users. Define and drive architecture strategy, making key technical decisions that shape the future of the platform. Architect and evolve Smartsheet's Identity and Access foundation — spanning authentication, authorization, and identity lifecycle — ensuring it scales securely across enterprise, multi-entity, and regulated environments. Craft and drive the strategy for Agentic Identity, defining how AI agents authenticate, are authorized, and are audited across the platform, and establishing identity patterns for agent-to-service and agent-on-behalf-of-user flows. Review and guide technical project designs, providing feedback during design review presentations to ensure system resilience and scalability. Take ownership of cross-functional technical initiatives, aligning teams around common architectural goals while driv

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Snowflake
📍 United States Minor Outlying Islands, United States• Full-time• Remote
1mo ago

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Security Engineer, dedicated to Product Security Incident Response. In this role, you will lead and architect Snowflake's product-integrated Incident Response strategy, with a primary focus on AI and LLM security. You'll design, plan, and drive the implementation of incident response capabilities across Snowflake's AI product surface - including Cortex AI, Cortex Agents, Snowflake Intelligence, and the data pipelines that power them. AS A SENIOR SECURITY ENGINEER, INCIDENT RESPONSE AT SNOWFLAKE, YOU WILL: Lead incident response for product-level security events, with deep focus on AI-specific threat vectors including prompt injection, model abuse, agent hijacking, and data exfiltration through AI workloads. Integrate IR into AI product pipelines - work directly with teams shipping Cortex features, Snowflake Intelligence, and AI-powered developer experiences to embed security requirements from design through deployment. Develop and codify our AI abuse response strategy - defining detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks targeting Snowflake customers. Address tech debt across the AI product stack, ensuring that new Cortex and agentic architectures meet IR readiness requirements from th

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Snowflake
📍 Menlo Park• Full-time• Remote
1mo ago

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Security Engineer, dedicated to Product Security Incident Response. In this role, you will lead and architect Snowflake's product-integrated Incident Response strategy, with a primary focus on AI and LLM security. You'll design, plan, and drive the implementation of incident response capabilities across Snowflake's AI product surface - including Cortex AI, Cortex Agents, Snowflake Intelligence, and the data pipelines that power them. AS A SENIOR SECURITY ENGINEER, INCIDENT RESPONSE AT SNOWFLAKE, YOU WILL: Lead incident response for product-level security events, with deep focus on AI-specific threat vectors including prompt injection, model abuse, agent hijacking, and data exfiltration through AI workloads. Integrate IR into AI product pipelines - work directly with teams shipping Cortex features, Snowflake Intelligence, and AI-powered developer experiences to embed security requirements from design through deployment. Develop and codify our AI abuse response strategy - defining detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks targeting Snowflake customers. Address tech debt across the AI product stack, ensuring that new Cortex and agentic architectures meet IR readiness requirements from th

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Coder
📍 United Kingdom• Full-time
1mo ago

As an Engineering Manager on Coder’s Agentic Engineering team, you’ll lead engineers building and evolving the systems behind our agentic development experience. You’ll help make agents more capable, reliable, and useful across real development environments. You’ll guide technical direction, grow the team, and keep execution sharp. You’ll work closely with Engineering, Product, and Design across the agent harness, integrations, and developer workflows. What you’ll do here Lead and grow a team within our Agentic Engineering organization. Set technical direction across the agent harness, integrations, and workflows. Stay close to the code and contribute to architecture and implementation decisions. Evolve agent execution, tool use, context management, streaming, and long-running workflows. Extend our provider-agnostic architecture as models and capabilities change. Partner with Product and Design to turn agent capabilities into useful developer experiences. Improve reliability, performance, and operability across agentic systems. Coach engineers, raise the technical bar, and create clarity around priorities and tradeoffs. What we’re looking for Experience managing and growing software engineering teams. Strong hands-on engineering 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. Strong technical judgment and comfort working through ambiguity. A track record of helping engineers grow while maintaining a high execution bar. 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 enviro

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Sentry
📍 San Francisco• Full-time• $220K – $450K/yr
1mo ago

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 AI and machine learning are reshaping how developers debug, monitor, and ship software, and Sentry is uniquely positioned to lead that shift. We sit on a novel and massive dataset of real production errors, spans, and logs from tens of thousands of engineering organizations — the kind of signal that makes ML genuinely useful, whether it's a clustering model that groups related issues, a ranking system that surfaces the right alert at the right time, or an agent that proposes a fix. We're looking for an Engineering Manager to lead and grow our Machine Learning Engineering team. This team owns the full spectrum of ML at Sentry: classical techniques like clustering, ranking, anomaly detection, and embeddings that quietly power core product surfaces today, alongside the LLM-based and agentic systems shaping where the product is headed. You'll partner closely with product, design, and engineering leaders to decide where ML belongs in our products, what kind of ML actually fits the problem, and how we translate that work into experiences millions of developers rely on every day. In this role you will Set technical direction across the team's full ML surface area — from classical models for clustering, ranking, and anomaly detection to LLM-based and agentic systems — and make sharp calls about which approach fits each problem Define how the team evaluates and monitors ML systems in production, from offline metrics to online experimentation to model and agent observability Stay hands-on enough to review code and model designs, contribute to architecture discussions, and unblock engineers on complex ML problems Define

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Ramp
📍 New York• Full-time• From $10K/yr
1mo ago

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role Ramp's Dev API team builds the programmatic surfaces that let developers and AI agents read from and write to Ramp. We are an AI-focused platform team making it trivially easy for any engineer at Ramp (or outside it) to ship new capabilities across all surfaces. Our ideal candidate thinks agent-first, has strong opinions on developer experience, and wants to define how software interacts with financial infrastructure at scale. Check out our Engineering Blog for more on our tech stack, mission, and values! What You'll Do Build and operate Ramp's multi-surface platform with a high bar for reliability, correctness, and developer experience across tens of thousands of businesses. Serve thousands of builders and partners using our API, driving a large fraction of Ramp’s revenue, and deliver on a massive business opportunity to embed Ramp everywhere. Build software factories -- autonomous tooling and agents that accelerate endpoint creation, enabling teams across Ramp to ship their own API surfaces. Lead design and execution of complex back

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R
1mo ago

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About this role: Accelerate engineering velocity and reduce friction in the Replit development experience by stewarding our codebases, tooling, and developer workflows. You will directly impact every engineer who ships code at Replit. By focusing on developer experience, you will act as a force multiplier across all product development teams, enabling faster feature delivery, happier developers, and reduced operational overhead. The role combines the technical depth needed to navigate a complex, polyglot codebase with the product mindset to understand how infrastructure decisions impact developer productivity and ultimately customer value delivery. You will also partner closely with the AI team on our internal AI platform — which already generates more than 60% of all merged PRs at Replit — to improve the Agent's output and help shape strategy around the Agent's default stack. This is an early hire in this area, so you will have agency and have an accelerated career path as the team undoubtedly grows. You will: Maintain and evolve our codebase structure — a complex TypeScript monorepo, Go services, npm packages, and internal Agentic tooling. Own the build and test pipelines and optimize them to minimize build times and improve developer iteration speed. Drive code generation and type-safe interfaces across service boundaries (e.g., GraphQL, Protocol Buffers, gRPC, OpenAPI). Set the standards for code quality using automation tools such as TypeScript, ESLint, Prettier, and Go linters/formatters — building custom rules and plugins to enforce Replit-specific requirements. Streamline development setup and the onboarding experience. Work with platform teams to improve deployment processes, infrastructure integrations, and e

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G
1mo ago

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Senior Backend Engineer on the Plan: Spec-Driven Development team, you'll help build GitLab's intent-to-code loop: agentic workflows that turn a stated intent into a refined work item, an implementation plan, and verified, mergeable code. You'll own early-stage backend work across the flows, application programming interfaces, data models, and evaluation systems behind this experience, using Ruby on Rails, Python, PostgreSQL, GitLab Duo Agent Platform, large language model application programming interfaces, and an artificial intelligence gateway. You'll join a small, distributed team working on one

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Datadog
📍 New York• Full-time• From $156K/yr
1mo ago

The Team We are Datadog’s in-house product experts. The Technical Solutions team enables Datadog’s worldwide growth by educating potential partners and ensuring that our integration ecosystem is high-performing, secure, and valuable. Partner Technology Solutions Engineers (TSEs) are the technical bridge between Datadog and our third-party developer community. We act as consultants, helping partners build world-class monitoring solutions on the Integration Developer Platform (IDP) . The Opportunity Datadog is looking for a Partner Technology Solutions Engineer to join our fast-paced team. You will be the primary technical contact for our partners, guiding them through the entire integration lifecycle—from initial architectural design to final publication on the Datadog Marketplace. This is a unique role that combines deep technical troubleshooting with high-level consulting and platform advocacy. You will work directly with external developers and see your contributions immediately reflected in the Datadog ecosystem. You Will Act as the technical lead for partners, advising on OAuth flows, log pipelines, OpenTelemetry, and agent-based vs. API-based configurations Perform architectural assessments and deep-dive code reviews for partner integrations in the integrations-extras and marketplace repositories, ensuring they meet our Quality Rubric Solve complex technical challenges for partners via Zendesk, Slack, and dedicated technical consultations Identify friction points in our Integration Developer Platform (IDP) and partner with our internal Product and Engineering teams to build a better developer experience Maintain public-facing developer documentation and internal tracking systems ( JIRA ) to ensure transparency and scale You Are A technical expert with 3+ years of experience in a technical role (Support Engineering, Solutions Architecture, or Software Development) Proficient in at least one language (Python or Go preferred) An observability enthusiast who unders

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Pinterest
📍 US; Remote, United States• Full-time• Remote• From $177.2K/yr
1mo ago

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 . The Conversion Visibility pod enables a performant ads marketplace and helps prove value to advertisers by connecting on-Pinterest intent with offsite conversions in a privacy-preserving way. We are hiring a Staff Software Engineer to lead the backend architecture and implementation of a GenAI-powered Conversion Health agent, using Event Quality Scores and conversion data to proactively detect issues, recommend and automate fixes, and demonstrate measurable performance impact for advertisers. What you’ll do: You’ll operate in a forward-deployed style , partnering directly with internal downstream teams that consume our conversion signal data to understand their workflows, build tailored solutions, and own them end-to-end from design through integration and iteration. Own the design and implementation of the Conversion GenAI agent: se

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Coinbase
📍 Brazil• Full-time• Remote
1mo ago

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 Software Engineer on the CX Shared Agent Platforms and SFDC Solutions team, you'll build and extend the platforms that power customer service and compliance operations across Coinbase. This team, part of the Enterprise Applications and Architecture org, owns CX tooling including Salesforce, Maestro QA, and Assembled, enabling agents to resolve customer issues and manage KYC workflows with speed and accuracy. You'll develop full-stack services and integrations that drive agent productivity, support strategic platform transitions, and deliver impact at scale from Brazil. What you'll do: Build and ship backend services using Golang and gRPC that extend CX platform capabilities and support agent workflows across compliance and consumer teams. Own the evaluation, integration, and ongoing support of third-party SaaS platforms, ensuring seamless connectivity across the CX tooling ecosystem. Partner with product, design, security, and data teams to deliver cross-functional solutions to complex operational and compliance challenges. Drive engineering best practices across the team, including code reviews, testing strategies, deployment processes, and observability standards (metrics, logging, tracing). Translate complex technical concepts into clear recommendations for non-technical stakeholders across CX, product, and leadership teams. Required Skills and Experience: 5+

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Coinbase
📍 - USA• Full-time• Remote• From $186.1K/yr
1mo ago

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 (EAA) The EAA Compliance CXAE team, part of Coinbase's Enterprise Applications and Architecture org, builds AI-first surfaces, tools, and applications that streamline compliance processes and improve the efficiency and effectiveness of Compliance agents. As a Senior Software Engineer, you'll build full-stack applications that enable Coinbase Compliance Agents to increase productivity, drive automation, and deliver impact at scale through custom development and third-party integrations. What you'll do: Build end-to-end user-facing features using Golang, React, and cloud technologies, delivering AI-first compliance tooling that improves agent productivity and KYC process accuracy. Lead assessment, selection, and implementation of third-party tools and vendor integrations into the compliance agent experience platform. Drive cross-functional delivery of complex technical solutions in collaboration with product, design, security, data, and peer engineering teams. Architect platform improvements that build upon existing development practices and technical domains, delivering reusable capabilities that benefit multiple teams across the organization. Own reliability for Tier-1 compliance systems by anticipating potential issues before they reach production and adapting your approach proactively to work within constraints. Mentor engineers in f

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Coinbase
📍 - India• Full-time• Remote• From ₹66.1L/yr
1mo ago

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 team is part of Coinbase’s Enterprise Applications and Architecture org and builds the customer-facing and internal CX experiences that connect the Help Center, chatbots (CBCB), and agent workflows. The team owns the multi-agent platform which powers coinbase chat, Help Center and agent tooling surfaces, partnering closely with Conversation Design, CX, and other Engg teams to deliver secure, compliant, and scalable AI-powered support. Our work provides the trusted and accurate automated and agent-assisted experiences—helping customers get answers faster while enabling human agents to resolve cases more effectively. We are hiring an IC5 Machine Learning Engineer to drive the evolution of our conversational ecosystem by building a seamless hybrid vendor-internal chatbot experience. You will lead the design and implementation of a sophisticated unified orchestration layer that coordinates interactions between vendor AI, internal multi-agent systems, and human participants. This role is pivotal in managing complex state transitions, context sharing, and intent routing across a distributed environment. You’ll thrive here if you enjoy high ownership, architecting complex hand-off logic between disparate LLM frameworks, and building reliable AI-enabled products that are fast, measurable, and scalable. What you'll do: Architect and deploy the orchestratio

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OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of this API & power-users team, you will improve the capabilities, reliability, and product fit of OpenAI’s agentic models for power users and API developers. You might design evals from real developer workflows, build training environments around production-like tool use, turn qualitative model failures into training data, evals, or post-training interventions, or drive a behavior improvement from discovery through post-training, integration, and launch. This role is intentionally broad. The strongest candidates are comfortable turning ambiguous model behavior problems into concrete progress, whether that means improving tool use, planning, instruction following, recovery from mistakes, or how models behave in API-based workflows. You should be excited to work across research, engineering, data, evals, and product to make models better at acting in real workflows. You will work closely with researchers, engineers, API/product teams, Codex, infrastructure, and safety/align

awsrestai
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OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team The Codex Research team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of the Codex Research team, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measu

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