AI Engineer, LLM – GenAI

This is a fully remote position, open to applicants in India.

📋 Description

• Solution Architecture & Deployment: Create and implement secure, scalable GenAI architectures that are integrated into applications.

• Build and deploy REST APIs for AI/ML models.

• Utilize Docker and Kubernetes in cloud environments such as AWS, Azure, and GCP.

• GenAI & LLM Development: Fine-tune and enhance LLMs including GPT, VAEs, GANs, and transformer-based models.

• Implement RAG pipelines, embedding techniques, and prompt engineering.

• Work with both commercial and open-source LLMs including GPT, Claude, LLaMA, and Phi.

• Agentic AI Development: Create and deploy AI agents using LangChain, LangGraph, CrewAI, Autogen, and AgentFlow.

• Implement multi-agent systems, orchestration, tool integration, and state management.

• Develop autonomous or semi-autonomous workflows for various business use cases.

• MLOps & Optimization: Establish end-to-end MLOps pipelines including CI/CD, monitoring, and retraining processes.

• Optimize performance, scalability, and infrastructure costs.

• Utilize tools such as Git, Docker, Kubernetes, and vector databases.

• Application Development & Data Integration: Create APIs using FastAPI and Node.js.

• Work with React, TypeScript, async patterns, and WebSockets/SSE.

• Manage data integration through REST APIs, SQL, and external systems.

• Cross-Functional Collaboration: Collaborate with Engineering, Product, and Data teams.

• Clearly communicate complex AI concepts to both technical and non-technical stakeholders.

• Stay informed about the latest advancements in GenAI and AI agents.

⛳️ Requirements

• Strong proficiency in Python, SQL, and GenAI frameworks (e.g., LangChain).

• Hands-on experience with LLMs, RAG, embedding, and prompt tuning.

• Experience in building AI agents and multi-agent systems.

• Familiarity with cloud platforms (AWS/Azure/GCP) and containerization technologies.

• Solid understanding of REST APIs and data integration techniques.

• Experience with FastAPI, Node.js, React, and TypeScript.

• Knowledge of MLOps and deployment best practices.

• Strong analytical, problem-solving, and communication skills.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive insurance plans.

• Collaborative and supportive work environment.

• Opportunity to learn and grow with a talented team.

• A positive and enjoyable work atmosphere.