Description

You will define and operationalize the end-to-end AI engineering and delivery lifecycle, leading the AI delivery organization across engineering and operations.

Responsibilities

• Implement and standardize AI SDLC/ADLC processes, DevSecOps, AI Ops, and LLM Ops practices.
• Establish and track engineering KPIs to drive fast, iterative, outcome-focused delivery execution.
• Select and standardize AI tools, platforms, and frameworks while aligning with enterprise architecture standards.
• Ensure compliance with AI governance, security, and risk requirements throughout the development lifecycle.
• Structure and lead agile pod-based delivery teams to scale platform-driven engineering with reusable components.

Required Skills

• 5+ years of experience in AI/ML engineering or DevOps leadership.
• Deep expertise in DevSecOps, CI/CD pipelines, and SDLC methodologies.
• Proven track record of building AI platforms or ecosystems from scratch.
• Strong understanding of AI Ops and LLM Ops, including monitoring, evaluation, and drift management.
• Experience establishing engineering standards and KPIs in an enterprise environment.
• Ability to engage with executive stakeholders and cross-functional teams.

Preferred Skills

• Experience with guardrails and risk mitigation in production AI systems.
• Background in regulated industries requiring strict compliance standards.

Education: Any Graduate

Key Skills

Education

Any Gradute