Description
We’re looking for a Tech Lead to be the company-wide focal point for AI utilization, infrastructure, and security — across both our core compliance platform and the Agentic Suite. This is a hands-on technical authority role, not a management track: you'll lead a small team (2-5 engineers) while spending most of your time driving how the company builds with AI, not on people management. You'll report to the Agentic BU owner.
Responsibilities
Own the company's AI infrastructure — model access, tooling, evaluation, cost/performance tradeoffs — across all engineering teams
Drive AI-native R&D transformation: bring agentic development practices into day-to-day engineering workflows, not just the product
Own AI-related security posture: data handling, model/tool access control, secure use of third-party AI services
Be the go-to technical authority other teams pull in when adopting AI tooling or agentic patterns
Lead a small team (2-5 engineers) building and maintaining shared AI infra and tooling
Identify workflow inefficiencies across R&D and drive the infra/tooling changes that fix them
Requirements
5+ years leading engineering teams or technical initiatives at the intersection of infra, tooling, and delivery
Direct, hands-on experience driving an AI-native R&D transformation — not just using AI tools, but changing how a team builds with them
Proven track record of measurably improving R&D workflow efficiency (not just proposing it)
Strong technical depth in infrastructure and security — able to make and defend architecture-level calls
Comfortable operating as an individual technical leader — influence through expertise, not org size
Nice to have
Experience in a regulated or compliance-heavy environment
Background with agent frameworks (LangGraph or similar) and MCP-based tool architectures
Experience with AI infra security specifically (model access control, data isolation, audit logging for AI systems)
Summary
A hands-on tech lead owns the company's AI infrastructure and security posture, guiding model access, tooling, evaluation, and cost tradeoffs across engineering teams. They also lead a 2-5 engineer team and drive AI-native R&D workflow changes, requiring 5+ years leading engineering initiatives spanning infrastructure, tooling, and delivery.
Responsibilities
Own company's AI infrastructure, model access, tooling, evaluation, and cost/performance tradeoffs; drive AI-native R&D transformation; own AI-related security posture; lead small team of 2-5 engineers building shared AI infra and tooling; identify and fix R&D workflow inefficiencies
Qualifications
5+ years leading engineering teams or technical initiatives at the intersection of infra, tooling, and delivery; direct hands-on experience driving AI-native R&D transformation; proven track record measurably improving R&D workflow efficiency; strong technical depth in infrastructure and security
Experience requirements
5+ years leading engineering teams or technical initiatives at the intersection of infra, tooling, and delivery