Key Responsibilities
1. 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
2. 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)
3. 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
4. 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)
5. 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)
6. 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
7. Evaluation & Optimization
- Define metrics for:
- Developer productivity improvement
- Code quality and defect reduction
- Optimize for cost, latency, and accuracy of LLM usage
8. Governance & Security
- Ensure:
- Secure code handling and IP protection
- Compliance with enterprise AI governance
- Guardrails to prevent insecure or non-compliant code generation
Required Skills & Experience
Core Skills
- 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)
