Experience: 5-7 years
Job Summary:
We are seeking a highly skilled GenAI & Agentic AI Developer to design, develop, and deploy enterprise-grade AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and Agentic AI frameworks.
Key Responsibilities:
Design and develop Generative AI and Agentic AI solutions for enterprise use cases.
Build AI-powered applications such as chatbots, virtual assistants, knowledge assistants, copilots, and workflow automation platforms.
Work within Agile/Scrum teams and contribute to sprint planning, estimations, and delivery activities.
Generative AI & LLMsStrong understanding of Generative AI concepts and architectures.
Hands-on experience with Large Language Models (LLMs).
Experience working with OpenAI, Claude, Gemini, Llama, Mistral, or equivalent models.
Experience with Multi-Agent Architectures.Knowledge of Human-in-the-Loop (HITL) workflows and agent governance.
RAG & Knowledge SystemsDesign and implementation of RAG solutions.
Document ingestion, chunking, embedding, indexing, and retrieval strategies.
AI Frameworks, LangChain, LangGraph, LlamaIndex, CrewAI, AutoGenMCP (Model Context Protocol),AI Agent Orchestration Frameworks,Programming & APIs,Strong proficiency in Python.
REST API development and integration.,FastAPI or Flask,JSON, API Gateway, Authentication, and Security best practices.
Databases & Vector Stores:
SQL (PostgreSQL, MySQL, SQL Server, etc.)
Vector Databases:Pinecone,Weaviate,ChromaDB,FAISS,OpenSearch Vector Engine
CI/CD implementation using GitHub Actions, Jenkins, GitLab CI/CD, or AWS CodePipeline.
Docker and containerized deployments.
Required Qualifications:
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.
5–8 years of software engineering experience.
Minimum 2+ years of hands-on experience in Generative AI solution development.
Experience with Agent Evaluation Frameworks.
Knowledge of Model Fine-Tuning and Parameter-Efficient Fine-Tuning (PEFT).
Experience with Knowledge Graphs and Graph RAG.Experience in Healthcare, Pharma, Life Sciences, Financial Services, or Enterprise Digital Transformation programs.
Exposure to MLOps, LLMOps, and AI Governance platforms.