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 /
  
• 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 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 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
  

Required Skills:

GenAI Large Language Models (LLMs) GPT RAG (Retrieval Augmented Generation) Prompt Engineering AI Agents LangChain LangGraph CrewAI Autogen AgentFlow Python SQL REST APIs FastAPI Docker Kubernetes AWS Azure GCP Vector Databases Embeddings Transformer Models MLOps CI/CD Model Deployment AI Orchestration Multi-Agent Systems State Management WebSockets React TypeScript

Employment Type : Full Time
Experience: years
Vacancy: 1