• Strong full stack engineering mindset with GenAI expertise.
• Experience building production-grade AI systems.
• Ability to work across AI, backend, cloud, and DevOps stacks.
• Passion for building automation solutions powered by agentic AI.
Key Responsibilities
• Design and develop agentic AI applications that automate enterprise workflows and decision-making processes.
• Build scalable backend services using Python, FastAPI, and Pydantic.
• Develop and deploy LLM-powered applications using models such as GPT and Claude.
• Build AI agents and orchestration workflows using LangChain or Strands.
• Implement Retrieval Augmented Generation (RAG) solutions using vector databases (pgvector, Pinecone, Weaviate).
• Perform data analysis, preparation, and curation to build high-quality datasets for AI and knowledge retrieval systems.
• Design and implement document ingestion pipelines for enterprise knowledge sources such as SharePoint, Confluence, and Jira.
• Deploy AI workloads on AWS (Bedrock, ECS Fargate, S3) with proper security and scalability practices.
• Develop and integrate enterprise APIs using REST, GraphQL, WebSockets, and web services.
• Implement secure authentication and authorization using Ping Identity, OAuth2, OIDC, and SSO.
• Build user interfaces for AI applications using ReactJS or Streamlit.