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