AI Engineering Lead

Narba Consulting Pvt. Ltd.; Dadri; On-site; INR 4,000,000 - 8,000,000; Full time

Job summary

Narba Consulting Pvt. Ltd. in Noida (Hybrid) seeks an AI Engineering Lead to design, build and deploy production-grade Generative AI and Agentic AI solutions.

You will lead autonomous multi-agent systems and advanced RAG architectures across enterprise cloud ecosystems. The ideal candidate has 7–10 years of experience in AI/ML, strong backend skills in Python and FastAPI, and proven ability to integrate leading foundation models into business workflows.

Qualifications

• Strong Python backend skills with production experience.
• Hands-on with GenAI, LLM integration and RAG pipelines.
• Experience building multi-agent systems and enterprise AI apps.
• Familiarity with vector databases and observability tools.
• Knowledge of LLMOps, governance, and security controls.

Responsibilities

• Design, build and deploy production-grade Generative AI apps.
• Architect autonomous multi-agent systems and RAG pipelines.
• Integrate OpenAI, Azure OpenAI, Gemini, and other models.
• Establish LLMOps, governance and security guardrails.
• Develop high-performance REST APIs and observability.
• Mentor engineers and shape AI strategy.

Skills

Python

FastAPI

SQL/PostgreSQL

Git & CI/CD

LLMs

RAG

LangChain

LangGraph

CrewAI

MCP

Pinecone

ChromaDB

Weaviate

FAISS

LangSmith

Langfuse

OpenTelemetry

Docker

Kubernetes

Azure

AWS

Vertex AI

Databricks

Tools

LangChain

LangGraph

CrewAI

AutoGen

MCP

Pinecone

ChromaDB

Weaviate

FAISS

LangSmith

Langfuse

OpenTelemetry

Docker

Kubernetes

SageMaker

Bedrock

Vertex AI

Job description

AI Engineering Lead

Role Overview

We are looking for a highly skilled AI Engineering Lead (Senior AI/ML Engineer) with hands-on expertise in designing, building, and deploying production-grade Generative AI and Agentic AI solutions. In this role, you will lead the architecture and implementation of autonomous AI agents, multi-agent systems, advanced RAG architectures, and scalable AI platform workflows across enterprise cloud ecosystems.

Key Details

• Role Title: AI Engineering Lead
• Experience Required: 7--10 Years
• Work Location: Noida (Hybrid)

Key Responsibilities

• Enterprise AI Deployment: Design, build, and deploy production-grade enterprise Generative AI and Agentic AI applications.
• Multi-Agent Systems: Architect and implement autonomous multi-agent systems using frameworks such as LangChain , LangGraph , CrewAI , AutoGen , and MCP (Model Context Protocol).
• RAG Architecture: Develop and optimize Retrieval-Augmented Generation (RAG) pipelines leveraging vector databases (Pinecone, ChromaDB, Weaviate, FAISS).
• LLM Integration: Integrate leading foundation models (OpenAI, Azure OpenAI, Gemini, Anthropic, AWS Bedrock) into core business products and enterprise workflows.
• LLMOps & Governance: Establish robust LLMOps practices, prompt engineering frameworks, model evaluation, guardrails, security controls (RBAC, prompt injection protection), and AI governance standards.
• API Development & Observability: Build high-performance REST APIs using FastAPI and implement full-stack AI observability using LangSmith , Langfuse , or OpenTelemetry.
• Performance & Cost Optimization: Optimize AI application performance for latency, token efficiency, throughput, scalability, and operational costs.
• Leadership & Strategy: Partner with cross-functional stakeholders to translate complex business problems into AI-driven solutions while mentoring junior engineers and driving AI best practices.

Technical Skills & Qualifications

Mandatory Skills

• Programming & Backend: Python, FastAPI, SQL / PostgreSQL, Git & CI/CD
• AI & LLMs: Generative AI, LLM Integration, Advanced Prompt Engineering, RAG
• Agentic Frameworks: LangChain, LangGraph, CrewAI, Model Context Protocol (MCP)
• Vector Databases: Pinecone, ChromaDB, Weaviate, FAISS
• LLMOps & Observability: LangSmith, Langfuse, Agent Evaluation & Observability
• Cloud & AI Platforms: Azure (AI Services, OpenAI, ML), AWS (Bedrock, SageMaker), Google Vertex AI, Databricks

Preferred Skills

• Graph & Security: Knowledge Graphs (Neo4j, GraphRAG) and NVIDIA NeMo Guardrails
• Agentic & Infrastructure: AutoGen, OpenTelemetry, Docker / Kubernetes
• ML Platforms & Frameworks: PyTorch / TensorFlow, MLflow / Kubeflow
• Document Intelligence: OCR & Intelligent Document Processing (IDP)