Job Overview

We are looking for a talented AI Engineer with over three years of experience in Large Language Models (LLMs), Conversational AI, and Generative AI. The ideal candidate will have hands-on experience building intelligent systems with LangChain and LangGraph, with a focus on AI agents, retrieval-augmented generation (RAG), and autonomous reasoning pipelines.

You'll collaborate with cross-functional teams to design, implement, and optimize AI-driven solutions that enhance business processes and user experiences.

Roles & Responsibilities

Design, fine-tune, and deploy LLMs for production-ready applications.
Build AI agents and multi-agent systems using LangChain, LangGraph, and related frameworks.
Develop and integrate Conversational AI pipelines that deliver seamless, human-like interactions.
Implement Retrieval-Augmented Generation (RAG) architectures leveraging vector databases and document retrievers.
Collaborate with data engineers and product teams to design scalable, reliable, and efficient AI pipelines.
Develop and maintain APIs and backend services using FastAPI and modern software engineering practices.
Collaborate with data engineers and product teams to design scalable, reliable, and efficient AI pipelines.
Optimize model inference, latency, and scalability in cloud and containerized environments
Optimize model inference, latency, and scalability in cloud and containerized environments.
Stay current with advancements in LLMs, Agentic AI, and Generative AI ecosystems.

Required Skills

Strong proficiency in Python and experience with LangChain and LangGraph for AI agent orchestration.
Experience integrating LLMs via APIs such as OpenAI, Anthropic, or Google Vertex AI.
Solid understanding of prompt engineering, RAG pipelines, and tool-using AI agents.
Proficiency with PyTorch, Transformers (Hugging Face), and vector databases (e.g., Qdarnt, FAISS, Chroma).
Experience designing multi-agent systems or workflow-based AI agents using LangGraph or similar frameworks.
Knowledge of LLM evaluation, prompt optimization, and context management strategies.
Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes).

Preferred Qualifications

Familiarity with MLOps and continuous integration/deployment pipelines for AI systems.
Understanding of generative AI models for text, image, or multimodal outputs.
Familiar with traditional ML and computer vision.
Strong problem-solving, collaboration, and communication skills.

Qualifications

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
3+ years of hands-on experience in AI/ML model development and deployment.

Mid/Senior AI Developer