JavaScript AI Jobs

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Lead and grow a team of Forward Deployed Engineers (FDE) delivering production systems with frontier models. Own end-to-end delivery outcomes through clarity, speed, tight coordination, and technical quality. Codify effective practices into tools, playbooks, and roadmap inputs to create leverage for OpenAI and the wider developer community. Identify and raise early indicators with urgency from product behavior, customer environments, or delivery practices. Use judgment to decide when action is required. Set high performance standards for FDEs and support each individual's growth through direct, actionable feedback. Define staffing and support strategies for scalable field teams without added complexity.

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Lead and grow a team of Forward Deployed Engineers delivering production systems with frontier models; own end-to-end delivery outcomes through clarity, speed, tight coordination, and technical quality; codify effective practices into tools, playbooks, and roadmap inputs to create leverage for OpenAI and its developer community; notice and urgently raise early indicators related to product behavior, customer environments, or delivery practices; use judgment to determine necessary actions; set high performance standards for FDEs and support individual growth through direct, actionable feedback; define staffing and support structures for scalable field teams without added complexity.

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Contribute to building Reinforcement Learning Environments (RLE) and supporting infrastructure; implement features across backend systems and frontend interfaces; work with senior engineers to improve system reliability and performance; help build modular workflow domains such as engineering, finance, and legal; support data pipelines that power model training and evaluation.

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The Senior Full Stack Software Engineer is responsible for owning technical delivery end-to-end, shaping the architecture of ML-powered applications, and leading implementation across cloud services, APIs, and modern front-end frameworks with Claude Code, the Claude Agent SDK, and the Claude API integrated into design, building, and shipping processes. They act as the technical backbone of their project pod, balancing hands-on development with technical leadership, architectural decision-making, and client-facing collaboration. Responsibilities include reducing project risk through proactive ownership of epic-level design and execution, improving technical decision-making via research and evaluation of solutions including AI tooling, increasing client confidence by leading technical discovery sessions and acting as a technical SME, leading feature and epic-level implementation, leading architecture and solution design for moderately complex solutions, championing AI engineering best practices within the pod, providing mentorship and technical leadership including code review and hiring assistance, engaging with clients for technical discovery and scoping, and implementing higher-level testing and quality strategies for deployed solutions and LLM-powered features.

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Collaborate with senior developers to design, build, and test software solutions for the agricultural sector. Contribute to coding, debugging, and documenting software applications. Assist in the development of new features from concept to deployment. Assist in research and development to improve the AI powered Assistant. Help optimize and improve the performance of existing software systems. Participate in code reviews and contribute to development process improvements and best practices. Test software functionality and troubleshoot issues. Collaborate with cross-functional teams such as product managers and data scientists to align technical solutions with business objectives. Stay updated with trends and technologies in software development and agriculture.

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You will own features end-to-end, holding a piece of work from contract through rollout across whichever surfaces it needs to touch, including the TypeScript/Node backend, the iOS app, the Android app, or all three. You will deliver the entire feature rather than handing off parts outside your domain. Early tasks include shipping meaningful production code on one of the products, defining and defending API contracts with mobile and design teams before implementation, and iterating on those contracts. You are expected to develop a point of view on the team's workflow and address inefficiencies, working across stack boundaries to deliver complete features and get them in front of real users.

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Serve as the primary technical subject matter expert on OpenAI Codex for a portfolio of customers, embedding deeply with them to enable their engineering teams and build coding workflows. Partner directly with customers to design and implement AI-enhanced development workflows, from rapid prototyping through scalable production rollout. Build high-quality demos, reference implementations, and workflow automations, using Codex itself as part of the development process. Lead large-format workshops, technical deep dives, and hands-on enablement sessions that help engineering organizations adopt AI coding tools effectively and safely. Contribute technical content including examples, guides, patterns, and best practices to the OpenAI Cookbook to help the broader developer community accelerate their work with Codex. Gather high-fidelity product insights from real customer deployments and translate them into clear product proposals and model feedback for internal teams. Influence customer strategy and decision-making by framing how AI coding tools fit into their software development lifecycle, technical roadmaps, and organizational workflows. Serve as a trusted advisor on solution architecture, operational readiness, model configuration, security considerations, and best-practice adoption.

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Build and improve production RAG and LLM-based systems. Design and maintain data pipelines that integrate enterprise data sources at scale. Develop full-stack product features end-to-end, from Python backend through React/TypeScript frontend. Work on optimization and scheduling problems with real operational constraints. Build evaluation frameworks that measure whether AI systems are actually improving.

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The Senior Business Systems Architect is responsible for leading and innovating across the enterprise systems landscape by designing, implementing, and optimizing scalable business processes and systems integrations. This role involves collaborating with cross-functional teams to create seamless workflows across financial systems, supply chain, and customer-facing platforms while leveraging process automation tools and middleware solutions. Key responsibilities include architecting end-to-end solutions, managing complex system integrations, building a strategic roadmap for enterprise system enhancements, strategic leadership by collaborating with stakeholders to develop and execute scalable system roadmaps, solution design and implementation of advanced workflows and modules in platforms like NetSuite, Stripe, and Maxio, selecting and standardizing tools and systems to align with operational needs and long-term goals, managing integrations and optimizing iPaaS tools such as Workato and Mulesoft for data flow and automation, ensuring SOX compliance through internal controls and audits, troubleshooting complex issues, mentoring team members, and delivering actionable insights through reporting and dashboards to support decision-making.

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Forward Deployed Engineers lead complex end-to-end deployments of frontier models in production alongside strategic customers, owning discovery, technical scoping, system design, build, and production rollout. They operate across multiple deployments from prototype to stable production, build full-stack systems to deliver customer value, embed closely with customer teams to understand needs, guide adoption, scope work, sequence delivery, remove blockers, make trade-offs between scope, speed, and quality, contribute directly in code when necessary, codify working patterns into reusable tools and playbooks, share field feedback to help Research and Product teams improve models, and keep teams moving with clarity and follow-through.