AI Engineer II responsible for owning end-to-end technical architecture, defining reliability and verification strategies, leading client relationships, mentoring engineers, and driving high-stakes agentic AI projects from architecture to production.

What You'll Do

- Own Engagement Architecture: Set the end-to-end technical architecture for the client's agentic system.
- Define the Reliability Strategy: Own the eval, verification, and decision-trace strategy that gets the system to 99.99% reliability.
- Lead the Client Relationship: Serve as the technical face to senior client leadership and manage expectations.
- Grow the Team: Mentor L1 and L2 engineers and set technical standards.
- Shape How the Company Delivers: Collaborate with founders on technical and delivery decisions.

Must have 4–6 years of software engineering experience, including systems you architected and took to production at scale. Deep, hands-on experience building agentic or ML systems with LLMs — orchestration, evals, reinforcement learning,



and reliability. A track record of owning technical direction on ambiguous, high-stakes projects end to end. Proven ability to design verification and eval strategies that hold non-deterministic systems to a high reliability bar. Credible senior stakeholder management — able to hold technical conversations with client engineering leadership.

Experience mentoring engineers and setting technical standards for a team.

Good to have

Delivery experience in regulated, high-stakes enterprise domains — banking, MedTech, CPG, or industrial. A consulting, forward-deployed, or solutions-architecture background alongside robust engineering. Depth in in-environment deployment (Azure, AWS, Databricks), observability, and MLOps for agentic systems. Public work — patents, talks, open source, or writing that shows technical leadership.

📌 AI Engineer II (India)
🏢 CodeRound AI
📍 India