AI Engineer

This is a remote position.

We are seeking an AI Engineer with deep expertise in Large Language Models (LLMs) , Generative AI , and Agentic AI . In this role, you will work on real-world applications such as autonomous agents, retrieval-augmented generation (RAG), multi-agent collaboration, and intelligent copilots.

As a specialist in multi-agent systems , you will design, develop, optimize, and deploy intelligent agents capable of reasoning, planning, and collaborating within coordinated environments. You’ll collaborate cross-functionally to deliver production-ready AI solutions powered by the latest LLM and agentic frameworks.

Requirements

Responsibilities
- Design and implement agentic AI systems with capabilities in reasoning, planning, memory, and contextual tool usage.

- Build and maintain multi-agent orchestration systems with role-based reasoning, dynamic task allocation, and resilient communication protocols.

- Develop RAG pipelines to integrate enterprise knowledge into LLM workflows.

- Build performant, scalable, and efficient multi-agentic systems.

- Embed autonomous agents into real-world applications and digital products.

- Optimize for performance, scalability, and robustness in production environments.

- Leverage frameworks like LangChain and LangGraph for agent orchestration and memory management.

Basic Qualifications
- Proven ability to quickly prototype, iterate, and deploy AI-powered features.

- Strong analytical, communication, and collaboration skills.

- Passion for staying current with GenAI tools, LLM research, and best practices. Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.

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Proven minimum 1+ year of hands-on experience with Agentic AI and multi-agent systems in production or enterprise environments.

- Proficient in Python and modern software engineering practices.

- Practical experience with LangChain , LangGraph , and prompt engineering .

- Experience with retrieval-augmented generation (RAG) pipelines.

- Familiarity with agentic memory architectures and Model Context Protocol (MCP) .

- Comfortable working on Azure or other major cloud platforms.

- Experience with Docker , Kubernetes , or similar containerization technologies.

- Experience implementing guardrails for LLMs and agent-based systems.

- Understanding of data governance principles and how they apply in AI system development.

- Experience with evaluation metrics , performance tracing , and logging tools such as LangSmith or similar platforms.

- Familiar with HIL (human in the loop)

Originally posted on Himalayas