TypeScript AI Jobs

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Design, build, ship, and maintain core capabilities for North’s Agents & Automations platform. Build product and platform features that help users create, run, debug, evaluate, and improve agents and automations. Own features end-to-end, from technical design through implementation, testing, launch, and iteration. Work across the stack, from frontend product surfaces to backend systems, depending on what the product needs. Make practical technical decisions that balance speed, quality, depth, and user impact. Collaborate closely with product, design, modelling, customer-facing teams, and other engineers to define the right outcomes and ship measurable improvements. Use AI actively in your work, while staying intellectually engaged and accountable for the quality and reliability of what you ship.

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Design and deliver production-grade AI agents that are highly performant, reliable, and intuitive, driving revenue directly to Sierra's growth across industries like finance, healthcare, and commerce. Take complete ownership and autonomy in the Agent Development Life Cycle from initial pilot through deployment and continuous iteration, including building, tuning, and evolving AI agents in production environments while defining best practices. Work directly with leaders of large enterprises and cutting-edge startups to understand their business challenges and develop AI agents that transform their operations at scale. Guide the evolution of Sierra's core platform through customer interaction, surfacing unmet needs, prototyping new tools and features, and collaborating with research, product, and platform teams to shape AI agent development and Sierra's products.

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Build end-to-end product experiences that span frontend applications, backend services, agent workflows, cloud infrastructure, and developer tooling. Design AI-powered workflows that generalize across a wide variety of software engineering teams, languages, codebases, and development practices. Discover and implement novel ways to apply AI to eliminate friction throughout the software development lifecycle. Partner closely with product, design, and research to understand developer needs and rapidly translate insights into shipped product improvements. Work directly with users—including developers at OpenAI, open-source contributors, startups, and large enterprises—to understand pain points and validate solutions. Improve the reliability, observability, scalability, and performance of the systems and workflows you build.

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Build core primitives end to end including entity ownership, audit, authorization, and orchestration, ensuring the right actions are the default and incorrect actions are difficult. Own the domain model by turning Fluidstack's concepts of power, datacenters, and chips into composable entities that remain durable over time. Define interactions with external systems by interfacing with vendor systems and ingesting domain-specific formats such as KMZ, BIM, Revit, and vendor documents. Enable AI agents to be first-class operators of Fluidstack's systems by providing tools, guardrails, and audit trails to allow safe and effective operation beyond mere advice.

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As a Senior Full Stack Engineer at Siena, you will own meaningful parts of the platform end to end, taking ambiguous problems and working out the right approach to ship reliable, high-performance systems that real brands depend on every day. You will own features and systems across the full stack including frontend, backend, and infrastructure from problem definition through production. You will partner with product to break down ambiguous scope and ship in iterative, high-impact releases, make real architectural and design decisions in your area and explain the reasoning to the team, and integrate cutting-edge language models into enterprise customer workflows where reliability and safety are critical. You will solve hard engineering problems including API performance, microservices, and scaling across channels and brands. Additionally, you will maintain and improve AWS infrastructure with a DevOps mindset and contribute to raising the bar around you by sharing knowledge, reviewing thoughtfully, and helping teammates level up.

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Design and deliver production-grade AI agents that are highly performant, reliable, and intuitive, which are central and mission-critical to Sierra's growth across industries like finance, healthcare, and commerce. Take complete ownership and autonomy over the Agent Development Life Cycle (ADLC) from initial pilot through deployment and continuous iteration, including building, tuning, and evolving AI agents in production environments while defining best practices for ADLC. Partner with leaders at large enterprises and cutting-edge startups to understand their business challenges and build AI agents that transform their operations at scale. Collaborate with customers to guide the evolution of Sierra's core platform by surfacing unmet needs, prototyping new tools and features, and working with research, product, and platform teams to shape the future of AI agent development and Sierra's product.

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Build backend and infrastructure systems that extend OpenAI's API platform into cloud-native environments such as AWS. Design and ship cloud-contained products that allow customers to use OpenAI capabilities while keeping workloads and data within cloud environments. Help stand up cloud-hosted Codex experiences powered by the OpenAI Responses API. Build infrastructure and runtime abstractions for a stateful, cloud-optimized agentic platform. Partner closely with external cloud partners as well as internal teams across Codex, Research, and Safety Systems to translate emerging capabilities into production-ready systems. Improve the reliability, scalability, observability, and operational maturity of the services underpinning these products. Help shape the technical direction of a new and growing team as it scales from an early core group into a larger engineering organization. This role also involves building backend services, APIs, SDK integrations, authentication flows, and cloud service infrastructure that let developers use OpenAI capabilities in the cloud environments where they already build, and working across teams sometimes embedded with partner product groups to ship products quickly across multiple platforms at the same time.

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Build end-to-end features across backend and frontend that directly impact customer revenue. Work closely with design, product, and GTM to ship features from idea to production. Translate real-world workflows, including calls, scheduling, and dispatch, into scalable systems. Improve system reliability, performance, and developer velocity as the system scales. Learn fast by working directly with customers and iterating based on real usage.

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Build production AI workflows including agentic workflows over enterprise and government data with clear rules for model visibility, tool usage, and human review. Design context and grounding systems for models to provide relevant information without violating permissions or performance constraints. Work across backend services, APIs, async workers, data pipelines, internal tools, and product-facing surfaces. Engineer reliable LLM systems by building evaluations and feedback loops for model behavior and workflow outcomes. Own tracing and runtime visibility across models, context, tool calls, and generated outputs. Debug failures using context, traces, tool responses, user reviews, and production logs. Improve quality without compromising latency, cost, or security. Build reusable AI systems by creating shared primitives for context assembly, grounding, tool use, and reviewable outputs. Develop systems that turn domain-specific AI behavior into product infrastructure rather than one-off customer logic. Move quickly from prototype to production quality systems with founders and engineers. Lead through ownership and engineering quality by taking ownership of important product and platform surfaces without needing heavy direction. Write clean, maintainable code and create clear abstractions. Use tools like Claude Code, Codex, ChatGPT, Cursor, and similar to accelerate development while maintaining the same standards for generated and hand-written code. Treat LLMs as architectural components with failure modes and costs to manage, not just black boxes to call.

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Design, build, and launch end-to-end product experiences for image generation and image editing within ChatGPT. Develop highly interactive frontend experiences that make sophisticated AI capabilities feel intuitive, fast, and delightful. Build scalable backend services, APIs, and workflows that power image creation, editing, storage, sharing, and retrieval. Partner closely with researchers to rapidly prototype and productionize new multimodal capabilities. Collaborate with Product, Design, Data Science, and Engineering teams to identify high-impact opportunities and execute against them. Own projects from concept through launch, including technical design, implementation, experimentation, measurement, and iteration. Optimize performance across the stack, from frontend responsiveness and rendering to backend latency, reliability, and scalability. Design systems that can support millions of users generating and interacting with visual content simultaneously. Leverage experimentation and user insights to improve engagement, usability, quality, and product outcomes. Contribute to engineering best practices around architecture, testing, observability, developer productivity, and operational excellence. Help define the future roadmap for AI-powered creative tools and visual experiences.