Description

Key Responsibilities

•     Define and implement an end-to-end AI SDLC framework from requirements through development, testing, validation, and

•     deployment.

•     Build AI-driven reverse engineering processes to analyze existing applications, code, database, APIs, UI, and business rules and

•     convert them into structured specifications.

•     Establish Specification-Driven Development (SDD) where approved requirements/specifications drive architecture, code, test

•     cases, and documentation.

•     Design AI agent workflows for architecture, coding, SQL/data model, API, UI, testing, code review, and validation.

•     Implement AI-assisted forward engineering from BRD/FRD/specifications to production-ready application components.

•     Establish automated specification-to-code, specification-to-test, and traceability/validation mechanisms.

•     Define governance, security, quality gates, and human-in-the-loop controls for AI-generated artifacts.

•     Evaluate and integrate tools such as Claude Code, GitHub Copilot, Azure AI, OpenAI, or similar agentic development

•     platforms.

Required Skills

•     Generative AI, LLMs, RAG, AI Agents / Agentic AI

•     AI-assisted software engineering and SDLC automation

•     Reverse & forward engineering

•     Specification-Driven Development

•     Enterprise application architecture

•     .NET/Java, Angular/React, APIs, SQL, Python, Azure/Cloud

•     CI/CD, DevOps, automated testing

•     Prompt/context engineering and LLM evaluation

•     Strong understanding of software architecture, design patterns, and enterprise security

Preferred

•     Experience building an AI SDLC / Agentic Engineering framework from PoC to enterprise adoption.

•     Experience with legacy modernization and AI-based application parity/validation

Key Skills

Education

Bachelor's degree