We are looking for a forward-thinking GenAI / Agentic AI Engineer to build intelligent, multi-agent systems and production-ready AI solutions. You'll work with cutting-edge LLMs, RAG pipelines, orchestration frameworks, and vector databases to deliver next-generation automation, conversational agents, and AI-powered products.
Key Responsibilities
- Develop AI-powered applications using Python (primary) and JavaScript/TypeScript.
- Build agentic systems using modern frameworks: OpenWebUI, LangChain, LangGraph, LlamaIndex, smolagents, AutoGen, CrewAI, etc.
- Integrate LLMs from OpenAI, Anthropic, Meta, Mistral, and fine-tune workflows for local LLMs.
- Build and optimize chatbots, multi-agent workflows, and conversational flows.
- Design and implement RAG pipelines, including chunking strategies, embeddings, vector search, and retrieval optimization.
- Work with vector DBs such as ChromaDB, Milvus, Pinecone, Weaviate, Elasticsearch.
- Lead prompt engineering efforts and design function-calling/tool-calling schemas.
- Implement agent orchestration, memory systems, and context-management techniques.
- Build backend services and REST APIs using FastAPI, Flask, or Node.js.
- Deploy AI workloads using Docker, Kubernetes/OpenShift, and CI/CD pipelines.
- Handle unstructured datadocuments, PDFs, OCR outputsefficiently.
- Apply best practices for AI evaluation, hallucination reduction, and performance optimization.
- Partner with product and business teams to map real-world use cases into reliable AI agents.
- Produce clear technical documentation and communicate effectively with stakeholders.
Nice-to-Have Skills
- Experience with knowledge graphs or graph databases.
- Understanding of embedding optimization, model latency tuning, and advanced retrieval strategies.
- Familiarity with emerging GenAI tools, plugins, and evaluation frameworks.
Who You Are
You are passionate about the rapidly evolving AI landscape and love building intelligent, dynamic, autonomous systems. You bring a strong engineering mindset, curiosity for experimentation, and the ability to convert complex business problems into elegant AI solutions.
