Generative Ai 2- 5 yrs

Job Summary

We are seeking a skilled Generative AI Engineer to design, develop, and deploy enterprise-grade AI applications powered by Large Language Models (LLMs). The ideal candidate should have hands-on experience in developing AI solutions using OpenAI, Azure OpenAI, AWS Bedrock, LangChain, RAG architectures, vector databases, and modern cloud platforms.

Key Responsibilities

• Design and develop GenAI applications using GPT-4, Claude, Llama, Gemini, or similar LLMs.
• Build and optimize Retrieval Augmented Generation (RAG) pipelines.
• Develop Agentic AI and Multi-Agent systems using frameworks such as LangChain, LangGraph, AutoGen, or CrewAI.
• Implement prompt engineering techniques to improve model performance and response quality.
• Integrate vector databases for semantic search and knowledge retrieval.
• Build scalable APIs and backend services using Python and FastAPI.
• Fine-tune, evaluate, and monitor AI model performance.
• Integrate AI solutions with enterprise applications, databases, and cloud services.
• Implement AI guardrails, security controls, content filtering, and responsible AI practices.
• Collaborate with product, data engineering, and cloud teams to deploy production-ready solutions.

Required Skills

Generative AI / Agentic Ai

• Large Language Models (LLMs)
• Prompt Engineering
• RAG (Retrieval Augmented Generation)
• Agentic AI
• AI Agents and Multi-Agent Systems
• NLP Fundamentals

Frameworks & Libraries

• LangChain
• LangGraph
• AutoGen / CrewAI
• Hugging Face Transformers
• LlamaIndex

Programming

• Python
• REST APIs
• FastAPI
• Pydantic

Vector Databases

• Pinecone
• FAISS
• ChromaDB
• Azure AI Search
• Weaviate

Cloud Platforms

• Azure OpenAI
• Azure AI Search
• Azure Functions
• AWS Bedrock
• AWS SageMaker
• GCP Vertex AI (Good to Have)

Data & Databases

• SQL
• PostgreSQL
• Cosmos DB
• MongoDB
• Redis

DevOps

• Git/GitHub
• Docker
• CI/CD Pipelines
• Kubernetes (Preferred)

Preferred Experience

• Experience building enterprise chatbots, copilots, or knowledge assistants.
• Hands-on implementation of multi-agent workflows.
• Experience with semantic search, embeddings, reranking, and hybrid search.
• Exposure to monitoring tools such as LangSmith, Azure Application Insights, or Prompt Flow.
• Experience with AI governance, evaluation frameworks, and model observability.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Electronics, or related field.
• 2-6 years of software development experience.
• Minimum 2 years of hands-on experience in Generative AI/LLM projects.

Nice to Have

• Azure AI Engineer (AI-102)
• AWS Machine Learning Specialty
• Experience with ServiceNow, Microsoft Teams integrations, or enterprise workflow automation.
• Exposure to fine-tuning, LoRA, PEFT, and open-source LLM deployment.