Senior Gen AI Engineer / Overall 5+ years experience / Conversation AI - Chatbot Dev Experience

Overview

About the Role (GenAI Senior Engineer)

We are seeking a GenAI Engineer with 5+ years of experience and with strong expertise in Agentic AI development using LangChain and LangGraph, along with solid foundations in traditional Machine Learning and Deep Learning.

The ideal candidate will own and lead team to design, develop, and deploy AI-driven applications leveraging LLMs, Vector Databases, and GenAI frameworks to solve complex real-world problems.

Key Responsibilities
Design and implement conversational AI / chat solutions using frameworks
Design and implement Agentic AI workflows using LangChain and LangGraph for intelligent automation and reasoning-based solutions.
Develop scalable GenAI-powered APIs and microservices using Python and FastAPI.
Design and implement RAG-based solutions for client.
Collaborate with cross-functional teams to deliver production-grade GenAI solutions with high performance and reliability.
Apply AI Ops practices (LangFuse, Docker, Jenkins, Groovy) for deployment, monitoring, and CI/CD.
Build and optimize Machine Learning/Deep Learning models, understanding on hyperparameter tuning/ performance evaluation.
Stay current with emerging AI trends, frameworks, and best practices in Agentic and Generative AI systems.

Required Skills & Experience
5+ years of professional experience in AI/ML or GenAI development.
Design and implement conversational AI / chat solutions using frameworks
Hands-on experience with LangChain and LangGraph for Agentic solution design.
Experience working with Vector Databases (FAISS, Pinecone, Weaviate, or MongoDB).
Familiarity with LLMs (OpenAI, Azure OpenAI, Anthropic Claude, Meta Llama, etc.).
Deep understanding of Machine Learning algorithms – regression, decision trees, SVM, random forests, deep learning, and reinforcement learning.
Strong proficiency in Python and FastAPI.
Expertise with frameworks such as TensorFlow, PyTorch, scikit-learn, and Keras.
Strong foundation in mathematics and statistics (linear algebra, calculus, probability, and statistics).
Experience in SQL, data preprocessing, and feature engineering.

Good to Have
Working knowledge of AI Ops tools – LangFuse, Jenkins, Docker, Groovy, FitNesse, and CI/CD pipelines.
Experience in LLM fine-tuning.
Exposure to eRAG (Azure-based RAG solution).
Familiarity with prompt engineering and LLM observability tools.
Understanding on NFRs, solution architecture and deployment models

Experience: 5+ years in Gen AI
Location: Bangalore
Work Mode: Hybrid
Notice Period: Immediate joiners preferred, up to 30 days’ notice accepted