Agentic AI Engineer

Job Description

An Agentic AI Engineer designs, develops, and deploys autonomous agent systems that use advanced AI techniques to reason, plan, act, and collaborate, often employing large language models (LLMs), retrieval-augmented generation (RAG), and multi-agent frameworks to solve real-world business and technical challenges.

Responsibilities:

• Design and build agentic AI solutions that incorporate LLM orchestration, RAG pipelines, agent memory, context integration, and autonomous decision-making.
• Architect frameworks for multi-agent communication, agent flows, and dynamic task assignment using platforms such as LangChain, AutoGen, LangGraph, CrewAI, and OpenAI Swarm.
• Integrate AI agents into company workflows to automate, optimize, and revolutionize operations — including vendor management, customer service, and legal or compliance processes.
• Implement and manage observability tools (LangSmith, LangFuse, MLFlow) to monitor, debug, and continuously improve agentic behavior and reliability.
• Develop oversight mechanisms, balancing autonomy and safety through guardrails, human-in-the-loop systems, response verification, and prevention of hallucinations.

Requirements:

• Demonstrated experience building and deploying agentic AI systems, including multi-agent workflows and decision models using modern AI frameworks and vector databases (Pinecone, Weaviate, ChromaDB).
• Proficiency in Python and other AI/ML coding platforms, including integration of external APIs and tools for real-world automation.
• Practical knowledge of prompt engineering, memory management, semantic search, and orchestrating complex agent behaviors.
• Strong debugging, research, and analytical abilities paired with experience in both frontend and backend development for AI-enabled systems.
• Ability to collaborate with cross-functional teams of researchers, data scientists, engineers, and business stakeholders to evolve agentic solutions.
• Train and fine tune foundational models.

Typical Technologies:

• LangChain, LangGraph, Pydantic AI, CrewAI, AutoGen, OpenAI’s Swarm/Agents SDK.
• AWS/GCP/Azure for AI workflows and scalable deployments.
• Vector databases, RAG pipelines, and observability tools (LangSmith, MLFlow).
• Reinforcement learning, planning systems, VLMs for multimodal tasks.

Interested candidates can apply online or email your CV to [email protected]