AI Team Lead

The AI Team Lead is a hands-on engineering leader responsible for the technical health, quality, and execution of an engineering team.

This is a player-coach role. The AI Team Lead is not the team's architect or the person who makes every technical decision. Their job is to create an environment where engineers make good technical decisions that are explicit, documented when appropriate, and aligned with established patterns and precedent.

Success means building a team that does not depend on the AI Team Lead to make good technical decisions.

Technical Governance

Create a culture of distributed technical ownership and decision-making.
Drive the use of Architecture Decision Records (ADRs) for significant decisions.
Drive AI adoption across the team
Ensure decisions consider tradeoffs, risks, and existing architectural precedent.
Encourage engineers to lead technical design, providing guidance and challenge rather than prescribing solutions.
Drive engineering best practices across design, development, testing, security, observability, performance, and reliability.
Keep technical debt and architectural risk visible and actively managed.

Hands-On Engineering

Stay close to the code and systems the team owns.
Contribute directly to complex, high-risk, or strategically important work.
Participate in technical design and code reviews.
Pair with engineers on difficult problems and provide technical leadership during production incidents.

Hands-on work should focus where it provides the most leverage to the team, not on maintaining the capacity of a full-time individual contributor.

Team Leadership

Directly manage, mentor, and develop engineers.
Set clear expectations around quality, ownership, and performance.
Provide regular feedback and career development.
Develop engineers' ability to independently own technical design and decisions.
Participate in hiring, onboarding, and performance management.

Engineering Execution

Partner with Product Management to turn priorities into technically sound plans.
Ensure complex work receives appropriate technical discovery and design before development.
Surface technical risks, dependencies, and complexity early.
Balance delivery with technical debt, reliability, and long-term platform health.
Own the engineering execution and technical outcomes of the team.

Experience

Experience building and operating production agentic AI workflows using LangChain.
5+ years experience with Python and Next.js.
Familiarity with Angular and Single Page Application (SPA) development.
Experience with containers and cloud-native application patterns.
Strong understanding of CI/CD, automated testing, and modern software delivery.
Experience working within a DevOps philosophy, including ownership of deployment, observability, reliability, and production support.
Strong understanding of software architecture, APIs, data modeling, performance, scalability, and security.
Demonstrated experience leading technical decisions and developing engineers.

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