Artificial Intelligence Engineer

HappieHire; Bengaluru; On-site; INR 2,500,000 - 3,500,000; Full time

Job summary

HappieHire is seeking a Senior AI Engineer focused on GenAI, RAG, and Agentic AI to deliver production-grade AI solutions across GCP and Azure. The role blends hands-on development, design, cloud deployment, and mentorship.

You will build autonomous agent solutions, work with enterprise AI workflows, and guide junior engineers in a fast-paced, cloud-first environment.

Qualifications

• 6+ years of AI/ML engineering experience.
• Strong Python with ML frameworks (PyTorch, TensorFlow, Scikit-learn).
• GCP & Azure enterprise AI workloads experience.

Responsibilities

• Build RAG, autonomous-agent, and multi-agent solutions using LangGraph, LangChain, MCP, and prompt engineering.
• Develop enterprise AI workflows with n8n, Python code nodes, APIs, databases, and external systems.
• Work with Gemini and Vertex AI, including Agent Builder, Model Garden, and Vertex AI Search & Conversation.
• Data cleansing, chunking, embeddings, vector search, and CDC-based real-time data synchronization.
• Develop and deploy AI services using Python, FastAPI, Docker, and Kubernetes/GKE.
• Fine-tune LLMs/SLMs such as Gemma using PEFT, LoRA/QLoRA.
• Evaluate models for quality, performance, latency, and cost.
• Build AI interfaces using Gradio/Streamlit.
• Support CI/CD, MLOps/LLMOps, monitoring, and production deployments.
• Collaborate with engineering and business teams and mentor junior AI/ML engineers.

Skills

Python

PyTorch

TensorFlow

Scikit-learn

GCP Experience

Azure Experience

LangGraph

LangChain

MCP

RAG

Agentic AI

PEFT

LoRA

QLoRA

Model evaluation

Vector stores

CDC data

APIs

Databases

Tools

n8n

FastAPI

Docker

Kubernetes

GKE

Gradio

Streamlit

Vertex AI

Gemini

API integration

Job description

Role: Senior AI Engineer – Agentic AI & Generative AI

Experience: 6+ Years

Work Mode: Work from Office

About the Role

We is looking for a Senior AI Engineer to build production-ready GenAI, RAG, and Agentic AI solutions across GCP and Azure. The role combines hands-on development, solution design, cloud deployment, and technical mentoring.

What You’ll Do

• Build RAG, autonomous-agent, and multi-agent solutions using LangGraph, LangChain, MCP and prompt engineering.
• Develop enterprise AI workflows with n8n, Python Code Nodes, APIs, databases, and external systems.
• Work with Gemini and Vertex AI, including Agent Builder, Model Garden, and Vertex AI Search & Conversation.
• Perform data cleansing, chunking, embeddings, vector search, and CDC-based real-time data synchronization.
• Develop and deploy AI services using Python, FastAPI, Docker, and Kubernetes/GKE.
• Fine-tune LLMs/SLMs such as Gemma using PEFT, LoRA/QLoRA.
• Evaluate models for quality, performance, latency, and cost.
• Build AI interfaces using Gradio/Streamlit.
• Support CI/CD, MLOps/LLMOps, monitoring, and production deployments.
• Collaborate with engineering and business teams and mentor junior AI/ML engineers.

Key Skills

• 6+ years of relevant AI/ML Engineering experience.
• Strong Python with PyTorch, TensorFlow, or Scikit-learn.
• GCP & Azure experience with enterprise AI workloads.
• LangGraph, LangChain, MCP, RAG, Agentic AI.
• PEFT, LoRA/QLoRA, model evaluation and optimization.
• Experience with APIs, databases, vector stores, and CDC.
• Strong communication, problem-solving, and stakeholder management skills.

Preferred: Relevant AI/ML certifications and experience working on large-scale production AI solutions.