AES - DE - Generative AI Prompt Engineers

• *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)**