Description

Must Have Technical/Functional Skills:

· Proven experience as an AI Architect defining enterprise AI architecture, standards, and governance.

· Hands-on experience designing/building agent-based approaches and autonomous workflows.

· Strong expertise in Prompt Engineering (Zero/Few-shot, Chain-of-Thought) and prompt design.

· Strong Python development experience and ability to guide teams with reference implementations.

· Experience with RAG, vector databases, and cloud deployments.

· Practical experience with GitHub Copilot adoption patterns including guardrails, prompt library management, extensions, and metrics

Preferred / Nice to Have

· Experience designing enterprise adoption frameworks for Copilot/AI with change management and champion models.

· Experience building Copilot-led accelerators for engineering productivity and rapid prototyping.

· Knowledge of AI governance requirements and productionization practices.

Roles & Responsibilities

1) Architecture & Strategy (AI / Agentic AI)

· Define the overall solution architecture for enterprise agentic AI programs and create the target-state roadmap

· Establish AI architecture standards, reference patterns, and governance guidelines for adoption at scale.

· Design architecture across LLMs/frameworks, vector databases, and cloud deployments, including Responsible AI practices.

2) Autonomous Agent Design & Orchestration (Copilot-led)

· Architect and enable autonomous agent workflows using GitHub Copilot, including multi-step orchestration and enterprise guardrails.

· Define a framework for prompt libraries, guardrails, extensions/integrations, and productivity metric tracking for Copilot adopt

· Drive repeatable implementation approach and best practices for Copilot-based engineering interventions and productivity tracking

· Enable Copilot-driven acceleration from design artifacts (e.g., Figma requirement sheets) to boilerplate code and supporting assets, where applicable.

· Establish patterns for agent-assisted testing and a roadmap toward autonomous testing where feasible (e.g., test case generation, script automation, regression maintenance).

3) Prompt Engineering Excellence

· Own enterprise prompt strategy including Zero-shot / Few-shot / Chain-of-Thought prompting techniques and prompt governance.

· Create reusable prompt frameworks/cookbooks, templates, and standards for consistent outcomes across teams.

4) RAG + Model/Tool Orchestration (Python-led)

· Architect and govern RAG pipelines, knowledge grounding approaches, and multi-turn agent orchestration using frameworks such as LangChain (or equivalent).

· Provide hands-on guidance for implementation in Python, including reference implementations and integration patterns

Key Skills

Education

Any Graduate