Responsibilities

- Design and deploy agentic generative AI solutions leveraging LLMs, RAG pipelines, context engineering, and REST APIs.

- Architect and build multi-agent automation systems using frameworks such as LangGraph or similar orchestration platforms.

- Implement LLM governance architecture including prompt drift detection, auditability, and safety policies to ensure regulatory compliance.

- Develop and integrate vector database solutions for semantic search and retrieval-augmented generation.

- Collaborate cross-functionally with AI architects, product managers, and compliance teams to accelerate AI adoption across business units.

- Develop APIs using FastAPI/Flask and build interactive demos for stakeholder showcases.

- Contribute to MLOps practices including CI/CD pipelines, model monitoring, and deployment automation.





- Conduct research experiments to enhance model performance, reliability, and fairness.

- Build and maintain ML models for domain-specific tasks such as NLP, computer vision, and predictive analytics.

Required Qualifications Technical Skills

- Programming: Proficiency in Python; working knowledge of SQL and Java.

- GenAI LLMs: Deep expertise in LLMs, RAG, prompt engineering, fine-tuning, and model governance.

- Frameworks: LangChain.

- APIs Backend: FastAPI, Flask, REST API design.

- Databases: Vector databases (Milvus, PGVector), PostgreSQL.

- Cloud MLOps: Azure AI Foundry; Docker, Kubernetes, CI/CD pipelines.

- Visualization UI: Streamlit, basic UI/UX design principles.

📌 AI Development Engineer - Hyd/Ban (Hyderabad)
🏢 Pragma Edge Software Services
📍 Hyderabad