Senior AI Tech Lead

Role Overview

• Lead hands‑on technical execution for Agentic AI capabilities across PoC, MVP, and Production, ensuring delivery and production‑grade quality.
• Translate architecture and product intent into a clear build plan (components, sequencing, integration approach, technical risks), and drive implementation through the team.
• Define and enforce engineering practices: coding standards, PR/review quality bar, branching strategy, and “done” criteria for agentic workflows (including testability and operational readiness).
• Implement and guide development of key agentic components such as orchestration logic, tool/API integrations, retrieval patterns, guardrails, and human‑in‑the‑loop flows, ensuring they are reliable and maintainable.
• Own technical unblock and troubleshooting: resolve complex defects, integration issues, performance bottlenecks, and environment/build pipeline problems.
• Drive release readiness from a technical standpoint: dependency readiness, versioning, deployment checks, rollback considerations, and operational handover inputs.
• Ensure vendor‑delivered technical work is aligned to standards through review, integration oversight, and quality controls.
• Collaborate with QA/Validation to ensure the solution is testable and traceable, with appropriate evidence generation through the SDLC (unit/integration/system testing hooks, logs, artifacts).
• Partner with the Solutions Architect to ensure adherence to enterprise patterns, security/privacy expectations, and architectural constraints, escalating gaps early and proposing practical implementation options.
• Post‑release, drive reliability and performance tuning, manage technical debt, and improve observability to support ongoing stability of agentic behaviors in production.

Requirements

• 8+ 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.

Tech Stack

• Distributed Systems
• SDLC

Benefits

• Professional development opportunities
• Flexible working arrangements