Description
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

Required Skills & Experience
Core Skills
Solid program

📌 De&a Aiml Deep Learning Generative Ai Bengaluru
🏢 Zensar Technologies
📍 Bengaluru