AI Engineer (LLM / GenAI)
Key Responsibilities: Solution Architecture & Deployment: Design and deploy secure, scalable GenAI architectures integrated into applications Build and deploy REST APIs for AI/ML models Work with Docker, Kubernetes in cloud environments (AWS/Azure/GCP) GenAI & LLM Development: Fine-tune and optimize LLMs (GPT, VAEs, GANs, transformer-based models) Implement RAG pipelines, embedding, and prompt engineering techniques Work with commercial and open-source LLMs (GPT, Claude, LLaMA, Phi) Agentic AI Development: Build and deploy AI agents using LangChain, LangGraph, CrewAI, Autogen, AgentFlow Implement multi-agent systems, orchestration, tool integration, and state management Develop autonomous or semi-autonomous workflows for business use cases MLOps & Optimization: Set up end-to-end MLOps pipelines (CI/CD, monitoring, retraining) Optimize performance, scalability, and infrastructure costs Use tools like Git, Docker, Kubernetes, vector databases Application Development & Data Integration: Develop APIs using FastAPI / Node.js Work with React, TypeScript, async patterns, WebSockets/SSE Handle data integration using REST APIs, SQL, and external systems Cross-Functional Collaboration: Partner with Engineering, Product, and Data teams Communicate complex AI concepts clearly to technical and non-technical stakeholders Stay updated with the latest advancements in GenAI and AI agents Required Skills: Strong proficiency in Python, SQL, and GenAI frameworks (e.g., LangChain) Hands-on experience with LLMs, RAG, embedding, and prompt tuning Experience building AI agents and multi-agent systems Experience with cloud platforms (AWS/Azure/GCP) and containerization Strong knowledge of REST APIs and data integration Experience with FastAPI, Node.js, React, TypeScript Understanding of MLOps and deployment practices Strong analytical, problem-solving, and communication skills Preferred: 4+ years of experience with GenAI/LLMs in production Experience with agent orchestration frameworks (CrewAI, LangGraph, Autogen) Exposure to client-facing AI solutions or cross-functional projects Open-source contributions, research, or AI project portfolio
Requirements
Strong proficiency in Python, SQL, and GenAI frameworks (e.g., LangChain) Hands-on experience with LLMs, RAG, embedding, and prompt tuning Experience building AI agents and multi-agent systems Experience with cloud platforms (AWS/Azure/GCP) and containerization Strong knowledge of REST APIs and data integration Experience with FastAPI, Node.js, React, TypeScript Understanding of MLOps and deployment practices Strong analytical, problem-solving, and communication skills
Benefits
Competitive salary and performance-based bonuses. Comprehensive insurance plans. Collaborative and supportive work environment Chance to learn and grow with a talented team. A positive and fun work environment