Dot Compliance is a cloud based, innovative software company, and our product, built on Salesforce platform, allows life science customers to manage their quality and compliance.

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)