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 contemporary 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.

📌 Generative Ai 2- 5 yrs (Ahmedabad)
🏢 Infosys
📍 Ahmedabad