Software Engineering Tech Lead

About usWe're a forward deployed engineering studio. We embed with enterprise clients to help them figure out where AI actually belongs in their business, then build the systems that get them there. That means real problem solving and architecture work up front, and a paved path our clients' own teams can follow once we've built it. You'd be working alongside partners who've built at top companies like Meta, Amazon, and Airbnb, and who've founded venture-backed startups. Our clients are large enterprises with billions in revenue and real operational complexity. The roleYou'd be the senior technical voice on our engagements: owning architecture, setting the quality bar, and shipping. This is a small team. We need someone who can take an ambiguous problem and run with it, not someone who needs a backlog handed to them. What you'll ownArchitecture and technical direction across client-facing AI applicationsCode quality standards and review. You define what "good" means here and hold the lineInfrastructure: deployment, environments, cost and reliability of AI workloadsSecurity posture and getting through enterprise security reviewTechnical scoping. Telling us honestly what's buildable in the time we have, and what isn'tMentoring and raising the bar on more junior engineers What we're looking forRequired 8+ years building production softwarePrior tech lead experience. You've owned a system and a team's technical direction, not just ticketsStrong backend engineering (APIs, data pipelines, services)Hands-on infrastructure experience (cloud, CI/CD, deployment, observability)Practical security experience: auth, data handling, and passing enterprise security reviewGenuine interest in AI. You've built with LLMs, agents, or RAG and have opinions about where they work and where they don'tAbility to break down complex technical concepts into simple terms so stakeholders can understand Nice to have Experience in both startup and large company environments, so you know when to move fast and when process actually earns its keepEnterprise or consulting delivery experience, comfortable in front of a clientData modeling and ontology workMicrosoft 365, Azure, Copilot How we workSmall team, direct communication, short feedback loops. Two-week sprints. You'll work closely with product and design, and you'll have real say in what we take on and how we scope it. If you think something is a bad idea, we want to hear it early. Why this is interestingEnterprise AI adoption is mostly unsolved. Most of what's out there is pilots that never graduate. You'd be building the systems that do, for clients that are committed, well-resourced, and moving fast. The hard problems are real ones: data ontology, security, and proving any of it is working.