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
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