Description

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, databases, APIs, UI, and business rules and convert them into structured specifications.
• Establish Specification-Driven Development (SDD) where approved requirements and specifications drive architecture, code, test cases, and documentation.
• Design AI agent workflows for architecture, coding, SQL/data modeling, API development, UI, testing, code review, and validation.
• Implement AI-assisted forward engineering from business requirements documents, functional requirements documents, and 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.

Qualifications

• Required
  • Generative AI, LLMs, and RAG (Retrieval-Augmented Generation)
  • AI Agents and Agentic AI
  • AI-assisted software engineering and SDLC automation
  • Reverse and forward engineering
  • Specification-Driven Development
  • Enterprise application architecture
  • .NET or Java
  • Angular or React
  • APIs and SQL
  • Python
  • Azure or Cloud platforms
  • CI/CD and DevOps
  • Automated testing
  • Prompt and context engineering and LLM evaluation
  • Strong understanding of software architecture, design patterns, and enterprise security

Key Skills

Education

Bachelor's degree