Lead / Senior Fullstack Engineer (Good AI Adoption)

About the Role

We are looking for a pragmatic, adaptable, and seasoned Lead / Senior Fullstack Engineer to join our engineering team.

This is a hands-on individual contributor role. You'll design systems, write code, prototype ideas, debug the failures nobody else can reproduce, review the implementations that matter, and work alongside engineers and Tech Leads wherever deeper expertise is needed.

Your influence here won't come from managing people. It comes from the systems you improve, the technical decisions you shape, and the engineers who get better for having worked with you.

Modern AI-Native Workflow

We're building an AI-first engineering organization, and we want to get further than AI-assisted coding. You'll work with LLMs, AI APIs, agents, RAG, and evaluation, applied to problems in our own engineering and in the products we build for clients.

We're not trying to put AI into everything. We want to find the places where it pays off, build those properly, and write down what we learn so other teams can pick it up.

Technology Ecosystem & Philosophy

Our core platforms and products span a diverse tech ecosystem. We do not expect you to know all of these technologies, but we do expect you to have successfully navigated multiple tech stacks throughout your career and brought strong architectural insights along the way.

Key Responsibilities

• Own architecture and design decisions on the hardest systems in our portfolio
• Write code, prototype, and debug alongside the teams rather than from a distance
• Review the implementations that carry the most risk, and raise the bar through the work itself
• Find where AI pays off, build it properly, and turn what works into something other teams can reuse
• Work with Tech Leads on scalability, performance, reliability, and technical debt
• Evaluate new technology, prototype it, make a call, and write down the reasoning
• Work with clients and non-engineering stakeholders to turn vague problems into technical direction

What We Look For

• 7+ years building and running production software, and still writing code today
• Depth in system design and architecture: scalability, performance, distributed systems, reliability
• A track record of setting technical direction across several teams, or on one large and long-running program
• Quick to find your way around an unfamiliar codebase. Deep in at least one language and comfortable in several
• Hands-on experience with LLM-based systems. Things you have built, not only read about: AI APIs, prompt and context design, and at least one of agents, RAG, or evaluation
• Judgment about when not to build something, when to pay down debt, and when to say no
• The ability to mentor senior engineers and change their minds without formal authority
• Comfort working directly with clients and non-engineering stakeholders
• A habit of following where the field is going

Nice to have

• Production AI systems at scale: evaluation harnesses, guardrails, cost and latency tuning
• Depth in one of our domains: data platforms, cybersecurity, robotics, enterprise systems
• Internal tooling or platform work that made other teams faster
• Open source contributions, conference talks, or technical writing