Agentic AI Implementation Engineer

Job Title: Agentic AI Implementation Engineer

Location: Remote/Hybrid

Job Type: Full-Time

Experience Level: Mid/Senior-Level

Role Overview

We’re looking for a highly skilled and visionary Agentic AI Implementation Engineer who can design, build, and deploy intelligent systems using Agentic RAG techniques and custom GPTs. 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’s 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

• 3–6+ years of experience in software engineering, ML systems, or applied NLP/LLM development.
  
• 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).