Role Overview

This role focuses on designing and building advanced AI agents leveraging Generative AI and Large Language Models (LLMs) to enhance the entire Software Development Lifecycle (SDLC), focusing on developer productivity, code quality, and automation.

Responsibilities

AI Agents for Application Development: Design and build AI agents that assist in application development lifecycle (SDLC), including agents for code generation & scaffolding, API development & integration, and code refactoring and optimization. Enable developer copilots for faster feature delivery.
AI Agents for Application Enhancements: Build agents to analyze existing codebases, suggest enhancements or optimizations, automate bug detection and resolution, and 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, and 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) and 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) and knowledge repositories (Confluence, SharePoint).
DevOps & Integration: Integrate agents into CI/CD pipelines (Azure DevOps, GitHub Actions) and developer tools (IDE plugins, Copilot extensions). Develop APIs/microservices to expose agent capabilities.
Evaluation & Optimization: Define metrics for developer productivity improvement and code quality. Optimize for cost, latency, and accuracy of LLM usage.
Governance & Security: Ensure secure code handling and IP protection, compliance with enterprise AI governance, and guardrails against insecure code generation.

Requirements

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.
Experience building AI-powered developer tools or agents.
Strong knowledge of LLMs (OpenAI, Azure OpenAI, open-source models) and Prompt engineering & fine-tuning basics.
Experience in RAG-based solutions.
Hands-on experience with LangChain / Semantic Kernel / LlamaIndex, with exposure to AutoGen / CrewAI / multi-agent patterns.
Familiarity with GitHub / Azure DevOps repositories and CI/CD pipelines.
5–10 years total experience, with 2+ years in GenAI / AI-led development (preferred).