Job Description
We are looking for highly skilled NLP & LLM Experts to join our AI team and drive innovation in Agentic AI systems , focusing on reasoning, memory management, tool use, and multi-agent orchestration. This role is ideal for individuals who are passionate about building intelligent systems that go beyond traditional LLM applications — leveraging LangGraph , Model Context Protocol (MCP) , Retrieval-Augmented Generation (RAG) , and modular AI agents to power dynamic, context-aware applications. You’ll help shape the next generation of intelligent automation across domains such as customer support, internal tooling, and knowledge orchestration. Key Responsibilities Design and implement modular AI agents using frameworks such as LangGraph , enabling multi-turn reasoning, tool usage, and context retention. Build agentic workflows with Model Context Protocol (MCP) to manage dynamic memory, context injection, and action coordination. Develop and fine-tune LLMs (e.g., GPT-4, Qwen, LLaMA, Mistral) for downstream tasks such as multi-agent collaboration, structured generation, and reasoning. Integrate Retrieval-Augmented Generation (RAG) architectures with vector databases (e.g., FAISS, Milvus) to support context-aware responses and tool routing. Engineer prompts and multi-step reasoning chains for LLMs in agent-based environments. Deploy and optimize open-source LLMs using vLLM , Triton , or Ollama , ensuring low-latency inference at scale. Translate core NLP capabilities into production-ready agent behaviors, collaborating with engineering and product teams. Stay at the forefront of agentic AI research , contributing to internal frameworks and incorporating cutting-edge ideas from open source and academia. Present project outcomes and model behaviors to both technical and non-technical stakeholders to guide product strategy. Basic Qualifications Master’s, or PhD in Computer Science , Artificial Intelligence , or a related field. 2+ years of experience in AI or NLP-focused role
