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