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

DE&A - AIML - Deep Learning - Generative AI

Key skills