Design, develop, and deploy modular AI solutions using LLMs, RAG pipelines, and microservices
Build scalable, reusable “AI-in-a Box” accelerators for enterprise use cases
Develop APIs and AI agents for use cases such as summarization, Q&A, and chatbots
Define end-to-end solution architecture including ingestion, retrieval, orchestration, and deployment
Ensure modular, extensible, and production-ready design
Manage the full lifecycle from PoC to production deployment and optimization
Build data pipelines to ingest content from platforms like SharePoint and enterprise databases
Integrate AI solutions with enterprise tools such as Outlook, Teams, and Salesforce
Implement telemetry, logging, and evaluation frameworks
Mentor and guide junior team members

8–10 years of experience with demonstrated expertise in leading AI solution design, architecture, and delivery
Strong Python skills with experience in AI frameworks (LangChain, Transformers, OpenAI SDK, LLaMA APIs)
Hands-on experience with RAG pipelines, embeddings, and prompt design
Familiarity with Knowledge Graphs (Apache Jena, SPARQL)
Experience with Vector Databases (Pinecone, Chroma, etc.)
Knowledge of embedding models (OpenAI Ada, Cohere, BGE/E5) and reranking techniques
Experience building microservices (FastAPI, Flask)
Exposure to multi-agent frameworks (LangGraph, CrewAI, AutoGen)
Understanding of Model Context Protocol (MCP)
Cloud experience with Azure (AKS, App Service, ACI) and DevOps tools
Integration experience with enterprise platforms (Outlook, Teams, Salesforce)

Data Developer – Manager

Key skills