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August 20, 2026

Staff Engineer, AI Productivity

Senior • Remote

200,000 - 200,000 USD/yr

New York, NY

About the Role

We are looking for a Staff AI Productivity Engineer to accelerate how our engineering organization works with AI coding tools. This is a hands-on technical role focused on building infrastructure, tooling, and documentation that makes AI agents dramatically more effective across our codebase.

AI tools are evolving rapidly, and we believe the companies that invest in making agents truly productive—not just available—will have a significant advantage. You'll own this problem end-to-end: from setting up cloud development environments where agents can run autonomously, to building MCP integrations that give agents access to our internal systems, to creating the documentation and context that helps agents understand how we build software.

You'll have the hands-on acumen to do a lot of the heavy lifting yourself and the leadership skills to drive cross-team efforts to raise the bar everywhere. This role is a companion role to our Developer Productivity role but has a distinct focus: while Dev Productivity owns the build/test/deploy pipeline, you'll own the AI-assisted development experience. An exceptional candidate could wear both hats.

Some of the problems we'll be working on include:

  • Own the agentic development environment: Ensure agents can operate in independent cloud-based development environments, execute our full test suites, examine build results visually, and more.
  • Build our tooling integrations: Build MCP server integrations that connect our agents to the systems needed to build and debug software, such as CircleCI, Slack, Datadog, GitHub, and more.
  • Documentation and context: Own our repo-wide agents.md file and work with teams to ensure our library of agent guidance and skills is continually pushing the bar. Ensure our conventions and package structures are exposed in ways that agents can effectively use.
  • Enablement: Work with our engineers to understand where agents are struggling and address root causes such as better documentation and tooling access. Develop tooling for non-engineers to make simple visual updates to our application.
  • Serve as a “PM” for internal AI agents: Consistently keep us on the leading edge of AI productivity trends by staying abreast of state-of-the-art industry practices and driving those improvements across the organization.

We are looking for talented, intellectually curious, and motivated individuals who are interested in tackling the problems above. This is a senior role, but we focus on impact and potential for growth more than years of experience. The salary range for this position is $180,000–$400,000 USD per year, which is location independent in accordance with our remote-first policy. We also offer meaningful equity compensation in the form of ISO options, including early exercise and a 10-year post-termination exercise window.

About You

You are an engineer with a passion for solving hard technical problems that generate real value for customers. You're motivated by high ownership and are comfortable in a fast-paced, startup environment.

Must have

  • Strong software engineering fundamentals—you can dive into complex backend code and understand it quickly.
  • Deep hands-on experience with AI coding agents, such as Claude Code, Cursor, Copilot, Devin, or similar tools.
  • Experience writing effective agent documentation, custom instructions, or context files that meaningfully improved agent output.
  • Track record of building developer tools or infrastructure that other engineers actually use.
  • Comfortable working across the stack: you'll touch CI/CD, cloud infrastructure, internal tooling, and application code.

Nice to have

  • Experience building or contributing to MCP servers or similar agent-tooling integrations.
  • Background in developer productivity, platform engineering, or developer experience roles.
  • Experience with TypeScript/JavaScript monorepos, Go, and GraphQL.
  • Experience setting up sandboxed or containerized development environments at scale.

Interview Process

Our goal with the interview process is to balance speed with giving both parties opportunities to assess whether there is a strong mutual fit. Our technical interviews focus on how you design systems because we believe this is the best way for us to see how you work and for you to see how we collaborate. We don't ask you to write code to solve technical brainteasers that don't appear in your day-to-day job.

  • Apply: Run curl jobapi.hightouchdata.com on port 13784 and follow those instructions before applying.
  • Recruiter Screen (30m): Introductory call with the recruiting team to get to know each other and assess mutual fit.
  • System Design Screen (45m): Design a data-processing feature end-to-end.
  • AI Skills Interview (60m): Discuss how you leverage AI and how you've helped others do the same.
  • Hiring Manager Interview (45m): Discuss past experiences and future operating preferences to assess fit on values and operating principles.
  • System Design Interview (90m): Work with the interviewer to architect a system at a conceptual level, incorporating product, customer, and technical requirements.

E-Verify Statement

After you join the team, eligibility to work in the U.S. will be verified by submitting information from your Form I-9 to the Social Security Administration and, if needed, the Department of Homeland Security. This process happens post-hire only and is not used to pre-screen applicants.

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Remote

Warsaw, MZ, Poland

🏢 Summary: Full Stack Engineer role focused on building an AI-native assistant that delivers reliable, persistent, goal-oriented workflows. The position covers frontend, backend and AI integrations, including agent planning, external-tool use, LLM reliability and real-time interactions in a remote-first global team. 🗂️ Requirements: Professional full-stack engineering experience, Frontend and backend systems experience, System design expertise, Distributed applications knowledge, API architecture knowledge, LLM, RAG or AI-powered application experience, Production deployment ownership, Cross-functional collaboration with Engineering, Machine Learning and Product teams 📃 Skills: Next.js, Python, Node.js, PyTorch, OpenAI, Anthropic, LLMs, RAG, SQL, NoSQL, Kubernetes, Docker, APIs 🏢 Description: About the product Our client is developing an AI-native assistant designed to support everyday communication, organization, errands and complex workflows with minimal user input. The product must reliably manage long-running processes, retain context, interact with external tools and complete real-world tasks despite the non-deterministic nature of modern AI models. The company’s objective is to make everyday activities significantly faster and easier for users. About the role We are looking for a Full Stack Engineer specializing in AI systems to build the product layer that transforms advanced AI capabilities into useful, production-grade workflows. You will help design how AI agents plan and operate, interact with external tools, manage failures, recover from errors and deliver consistent value to users. This is an end-to-end engineering role covering frontend development, backend systems and AI integrations. What you will do Build end-to-end product functionality across frontend, backend and AI integrations. Design agent workflows covering planning, tool use, multi-step execution, failure handling and recovery. Integrate LLMs, memory systems and external tools into applications that operate reliably under real-world conditions. Design real-time AI interactions involving streaming, partial results and strict latency requirements. Improve system reliability, observability and fallback mechanisms. Collaborate closely with Machine Learning, backend and product teams to deliver functionality from concept to production. Continuously improve the product based on real-world usage, evaluation results and observed failure modes. What we are looking for Strong professional experience in full stack engineering across frontend and backend systems. Solid understanding of system design, distributed applications and API architecture. Experience working with LLMs, RAG systems or other AI-powered applications. Ability to operate effectively in ambiguous situations and make pragmatic engineering decisions. Strong ownership and the ability to take functionality from an initial idea through implementation and production deployment. Confidence working in a fast-moving environment with evolving product requirements. Ability to collaborate effectively across engineering, Machine Learning and product teams. What success looks like AI-native product features progress beyond basic chat interfaces into persistent, goal-oriented workflows. Agent workflows reliably complete multi-step tasks across external tools and multiple user sessions. AI interactions remain responsive and achieve low latency without compromising output quality. Production systems include robust fallback and recovery mechanisms for LLM and external-tool failures. The reliability and completion rate of AI workflows improve through continuous evaluation, monitoring and iteration. Reusable patterns and abstractions support scalable integration of LLMs, memory and external tools. The resulting product experience feels proactive, consistent and dependable to users. Technology stack Next.js Python Node.js PyTorch OpenAI, Anthropic and open-source LLMs SQL and NoSQL databases Kubernetes Docker Compensation and employment The position is offered under an employment contract. The company does not publish a fixed external salary range. Compensation is assessed individually based on: professional experience and technical capability, scope of responsibility, location and relevant market benchmarks, expected impact on the product and organization. Candidates may share their expected compensation at the beginning of the recruitment process. The compensation package consists of a base salary and equity, with flexibility for exceptional candidates. A company laptop will be provided where required for the role. Remote work and global collaboration The company operates as a remote-first, globally distributed organization. There is no fixed company-wide working schedule and no requirement to follow one specific time zone. Team members are expected to maintain sufficient working-hours overlap with their immediate colleagues to collaborate effectively. The successful candidate will work from Poland and collaborate with frontend, backend, Machine Learning and product specialists located across different regions. Poland-based employees join existing global teams rather than a separate local team. The exact reporting line and hiring manager will be confirmed during the recruitment process. How the team works The company believes that outstanding products are built by small, highly capable and hands-on teams. Decisions are made collaboratively, while individuals are expected to take ownership, bring structure to ambiguous problems and execute independently. The team moves quickly while balancing production quality, experimentation and continuous learning from real user behavior. There is no fixed hiring quota for this position. The company is focused on identifying engineers who meet its technical and ownership standards rather than filling a predetermined number of seats. Recruitment process The standard recruitment process consists of up to four stages: Technical assessment, where relevant to the candidate’s background. HR interview. One or more technical interviews. Founder or leadership interview. Particularly strong candidates may be fast-tracked directly to the technical interview stage based on their experience and previous work. Applications are evaluated by members of the technical team. Interviews may be conducted virtually and, where relevant, onsite. The exact format and interviewers may vary. The company aims to make decisions efficiently and provide candidates with a prompt outcome.