This is a hands-on role combining software engineering, ML/NLP expertise, and a passion for building next-gen autonomous agents. You’ll collaborate closely with AI leads, backend engineers, data engineers, and product managers to bring scalable and intelligent systems to life—integrated into real-world procurement and business applications.
Key Responsibilities
- Design and implement agentic AI pipelines using LangGraph, LangChain, CrewAI, or custom frameworks
- Build robust retrieval-augmented generation (RAG) systems with vector databases (e.g., FAISS, Pinecone, OpenSearch)
- Fine-tune, evaluate, and deploy LLMs for task-specific applications
- Integrate external tools and APIs into multi-agent workflows using dynamic tool/function calling (e.g., OpenAI JSON schema)
- Develop memory modules such as short-term context, episodic memory, and long-term vector stores
- Build scalable, cloud-native services using Python, Docker, and Terraform
- Collaborate in agile, cross-functional teams to rapidly prototype and ship ML-based features
- Monitor and evaluate agent performance using tailored metrics (e.g., success rate, hallucination rate)
- Ensure secure, reliable, and maintainable deployment of AI systems in production environments
