Agentic AI Engineer

We're looking for a highly skilled and visionary Agentic AI Implementation Engineer who can design, build, and deploy intelligent systems using Agentic techniques. This role will involve creating autonomous or semi-autonomous agents powered by LLMs that are capable of task planning, contextual decision-making, and iterative information retrieval.

You'll work at the intersection of advanced prompt engineering, tool orchestration, and multi-step reasoning, with a strong focus on performance, scalability, and user-centric design.

Key Responsibilities

• Architect and implement agentic workflows using RAG pipelines, LLM agents, and external tool integrations.
  
• Design modular, agentic systems that include planning, memory, tool use, and context-aware reasoning.
  
• Develop and optimize custom GPTs using advanced prompt engineering and OpenAI\u2019s custom instructions, functions, and APIs.
  
• Integrate knowledge bases, vector stores (e.g., FAISS, Pinecone, Weaviate), and APIs into a cohesive Agentic RAG architecture.
  
• Fine-tune agent behaviors for various real-world applications (e.g., customer support, research assistants, code agents).
  
• Collaborate closely with product managers, UX designers, and backend engineers to ship scalable and robust solutions.
  
• Rapidly prototype ideas, run LLM experiments, and iterate on designs using both quantitative and qualitative metrics.
  
• Monitor system performance, detect and address reasoning failures, hallucinations, and retrieval mismatches.
  
• Stay updated with the latest research and advancements in Agentic AI, RAG, tool use, and autonomous agents.

Must-Have Skills

• Strong expertise in Agentic RAG frameworks such as LangGraph, AutoGPT, CrewAI, LangChain Agents
  
• Proven ability to design and implement custom GPTs using advanced prompt strategies and OpenAI API (functions, tools, memory).
  
• Hands-on experience with vector databases (e.g., Cosmos DB, Pinecone, ChromaDB), embeddings, and semantic search.
  
• Deep understanding of retrieval augmentation , context compression, multi-hop querying, and memory management.
  
• Fluency in Python and experience with modern LLM tooling (e.g., LangChain, LlamaIndex).
  
• Strong systems thinking and ability to balance trade-offs between model performance, latency, and accuracy.
  
• Comfortable with fast-paced, iterative environments and exploratory development.

Desired Skills

• Experience with autonomous agents and frameworks like AutoGen, OpenAgents, or BabyAGI.
  
• Understanding of AI safety, ethics, and control mechanisms in agentic systems.
  
• Familiarity with evaluation techniques for LLM pipelines (e.g., hallucination detection, prompt testing frameworks).