We are seeking an AI Tech Lead to serve as a hands‐on technical leader for Agentic AI solutions across Proof of Concept, MVP, and Production.

Requirements

5+ years in software engineering roles with demonstrable hands‐on leadership as a senior developer, tech lead, or lead engineer delivering complex systems.
Proven experience leading technical execution across the SDLC, including integration, testing strategy support, and production release readiness.
Experience delivering AI‐enabled or data‐intensive products in regulated or enterprise contexts is strongly preferred.
Bachelor’s degree in a STEM field (Computer Science, Engineering, Data Science, Information Systems, Mathematics, or related discipline), or equivalent practical experience spanning product management, software delivery, and AI/data systems.
Strong engineering fundamentals in software design, APIs/integration, data flows, and distributed systems considerations.
Working knowledge of architecture principles (security, scalability, reliability, maintainability) and the ability to collaborate effectively with architecture teams to align implementation with standards and best practices.
Strong CI/CD and engineering hygiene: automated testing, code review discipline, environment readiness, and operational awareness.

Benefits

We are seeking an AI Tech Lead to serve as a hands‐on technical leader for Agentic AI solutions across Proof of Concept, MVP, and Production.

5+ years in software engineering roles with demonstrable hands‐on leadership as a senior developer, tech lead, or lead engineer delivering complex systems.
Proven experience leading technical execution across the SDLC, including integration, testing strategy support, and production release readiness.
Experience delivering AI‐enabled or data‐intensive products in regulated or enterprise contexts is strongly preferred.
Bachelor’s degree in a STEM field (Computer Science, Engineering, Data Science, Information Systems, Mathematics, or related discipline), or equivalent practical experience spanning product management, software delivery, and AI/data systems.
Strong engineering fundamentals in software design, APIs/integration, data flows, and distributed systems considerations.
Working knowledge of architecture principles (security, scalability, reliability, maintainability) and the ability to collaborate effectively with architecture teams to align implementation with standards and best practices.
Strong CI/CD and engineering hygiene: automated testing, code review discipline, environment readiness, and operational awareness.