AES - DE - Generative AI Prompt Engineers
Skills
About the role
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)
Questions about this role
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