DE&A - AIML - Deep Learning - Generative AI

Key Responsibilities

• AI Agents for Application Development
• Design and build AI agents that assist in application development lifecycle (SDLC)
• Develop agents for: + Code generation & scaffolding + API development & integration + Code refactoring and optimization
• Enable developer copilots for faster feature delivery
• AI Agents for Application Enhancements
• Build agents to: + Analyze existing codebases and suggest enhancements or optimizations + Automate bug detection and resolution + Support impact analysis for changes
• Develop agents for legacy modernization and code migration (e.g., Java/.NET upgrades)
• Testing & QA Automation Agents
• Create agents to: + Automatically generate unit, integration, and regression test cases + Perform test execution and defect prediction + Enable self-healing test automation frameworks
• LLM & Agent Framework Implementation
• Build solutions using frameworks such as: + LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI
• Implement: + Multi-agent orchestration (planner, executor, reviewer agents) + Tool-using agents (Git, CI/CD, APIs, databases)
• RAG & Context Engineering
• Implement RAG pipelines using application code repositories, documentation, and APIs
• Build context-aware agents using: + Codebases (GitHub, Azure DevOps) + Knowledge repositories (Confluence, SharePoint)
• DevOps & Integration
• Integrate agents into: + CI/CD pipelines (Azure DevOps, GitHub Actions) + Developer tools (IDE plugins, Copilot extensions)
• Develop APIs/microservices to expose agent capabilities
• Evaluation & Optimization
• Define metrics for: + Developer productivity improvement + Code quality and defect reduction
• Optimize for cost, latency, and accuracy of LLM usage
• Governance & Security
• Ensure: + Secure code handling and IP protection + Compliance with enterprise AI governance + Guardrails to prevent insecure or non-compliant code generation

Core Skills Required Skills & Experience

• Strong programming skills in Python (mandatory) and at least one of Java/.NET/Node.js
• Hands-on experience with application development & SDLC processes
• Experience with REST APIs, microservices architecture

AI / GenAI Skills

• Experience building AI-powered developer tools or agents
• Strong knowledge of: + LLMs (OpenAI, Azure OpenAI, open-source models) + Prompt engineering & fine-tuning basics
• Experience in RAG-based solutions

Agent Frameworks

• Hands-on with: + LangChain / Semantic Kernel / LlamaIndex + Exposure to AutoGen / CrewAI / multi-agent patterns

DevOps & Tools

• Familiarity with: + GitHub / Azure DevOps repositories + CI/CD pipelines + Docker / Kubernetes (preferred)

Good to Have

• Experience with GitHub Copilot or similar developer productivity tools
• Exposure to code analysis tools (SonarQube, SAST/DAST)
• Experience in legacy modernization projects
• BFSI domain experience (for enterprise use cases)

Experience

• 5–10 years total experience
• 2+ years in GenAI / AI-led development (preferred)