Key Responsibilities
- Design and develop AI-powered bots/agents to automate activities across the DataStage to Microsoft Fabric migration lifecycle, including assessment, code analysis, conversion, validation, and documentation.
- Develop and fine-tune LLM/GenAI models for understanding DataStage jobs, transformation logic, mappings, dependencies, and converting legacy ETL patterns to Fabric-compatible code.
- Build AI agents using Python, LLMs, RAG, prompt engineering, and agentic frameworks to support migration factory automation.
- Develop reusable AI solutions for DataStage code analysis, complexity assessment, code conversion, test-case generation, data validation, and defect/root-cause analysis.
- Integrate AI bots with enterprise tools, APIs, repositories, and migration platforms to enable automated workflows.
- Design evaluation frameworks to measure accuracy, quality, hallucination, conversion success rate, and model performance and continuously improve AI solutions.
- Build and maintain RAG solutions using enterprise migration documentation, code repositories, metadata, mappings, and technical knowledge bases.
- Collaborate with Data Engineers, Architects, QA Engineers, and Project Managers to identify and implement AI-driven automation opportunities.
- Implement secure, scalable, and production-ready AI solutions following enterprise Azure, security, governance, and CI/CD standards.
- Lead technical design, code reviews, POCs, and deployment of AI solutions and mentor junior AI engineers.
Required Experience
- 6-8 years of experience in AI/ML, Generative AI, NLP, or AI engineering.
- Strong hands-on experience developing AI bots/agents, LLM applications, RAG solutions, and prompt engineering.
- Experience with LLM fine-tuning/model customization and evaluating model performance.
- Strong Python development skills and experience integrating AI/LLM solutions through APIs.
- Experience with Azure OpenAI/Azure AI Services or equivalent enterprise GenAI platforms.
- Experience building AI solutions for code generation, code conversion, automation, or data engineering is highly desirable.
- Strong understanding of SDLC, Git, CI/CD, API integration, and production deployment.
Good to Have
- Prior experience with IBM DataStage, ETL, SQL, or Microsoft Fabric.
- Experience building AI solutions for legacy modernization, migration factories, or ETL/code conversion.
- Experience with LangChain, Semantic Kernel, AutoGen, or similar agentic AI frameworks.
- Experience with Github copilot and SLMs.
Industry:
AI & Machine Learning