Agentic AI and MCP - Technical Lead

Company Description

Nu10 is a New Yorkheadquartered AI company founded by three senior IITians with 70+ years of collective global experience building and scaling technology platforms. We are engineering the AI infrastructure layer for next-generation services in the BFSI domain architecting agentic systems, MCP-based integrations, A2A orchestration frameworks, voice-native AI, and enterprise-grade ML in highly regulated environments. Our work sits at the intersection of deep system design and real-world deployment where architectural clarity, performance, and robustness matter. If you are driven by first-principles thinking and want to build AI systems that operate beyond prototypes, Nu10 offers a platform worthy of your ambition.

Role Description

This is a full-time on-site role located in Bengaluru for a Technical Lead focused on Agentic AI and MCP architecture based projects. The Technical Lead will oversee the design, development, and implementation of technical solutions. Responsibilities include leading a team of developers, collaborating with cross-functional teams, conducting code reviews, troubleshooting and resolving technical challenges, and ensuring delivery within project timelines. The role will require a proactive approach in staying updated with AI advancements and contributing to innovative project solutions.

Experience: 48 years

Location: In Office, Indiranagar, Bengaluru

Reports to: CTO / Head of Engineering

Role Overview

We are looking for a Lead AI / GenAI Engineer to architect and build next-generation AI systems across conversational AI, document intelligence, agentic workflows, and voice interfaces.

We want someone who:

Understands LLM internals and system design

Can build production-grade AI pipelines

Can design clean component architectures

Can lead technical direction and mentor engineers

Thinks in abstractions, not hacks

You will work across the full stack of modern AI systems from RAG pipelines and vector databases to MCP integrations, A2A orchestration, and voice-based AI systems.

What Youll Build

Production-grade LLM-powered chatbots

RAG-based document processing systems

Intelligent knowledge retrieval systems

Agentic workflows (MCP, A2A patterns)

Voice-enabled AI systems (STT/TTS pipelines)

AI systems integrated with enterprise platforms

Scalable Python-based AI backends

Core Responsibilities

1 Architecture & Design

Design end-to-end AI/GenAI system architectures

Create clear component architecture diagrams

Design scalable RAG pipelines (chunking, embeddings, retrieval optimization)

Architect vector database strategies

Build modular, extensible AI systems

2 Engineering Leadership

Lead AI implementation across projects

Review code and enforce engineering standards

Mentor junior engineers

Collaborate closely with product and business stakeholders

Translate business requirements into technical flows

3 AI / GenAI Implementation

Hands-on expertise in:

LLM-based systems (OpenAI, Claude, Llama, etc.)

RAG architectures

Document parsing & chunking strategies

Vector databases (Pinecone, Weaviate, Milvus, FAISS, etc.)

Prompt design & evaluation

MCP-based architectures

Agent-to-agent (A2A) orchestration

Voice AI (STT / TTS integrations)

Model evaluation & guardrails

Technical Requirements

Must-Have

48 years of strong software engineering experience

Deep proficiency in Python

Strong system design fundamentals

Experience deploying AI systems in production

Hands-on with:

RAG pipelines

Embeddings & vector search

LLM APIs

Document processing

Experience working with REST APIs / async architectures

Ability to produce architecture diagrams & technical documentation

Good to Have

Experience with:

MCP frameworks

Agentic workflows

A2A patterns

LangChain / LlamaIndex

FastAPI / Flask

Kubernetes / Docker

Observability in AI systems

Voice AI (STT / TTS)

Experience optimizing token usage & latency

Exposure to fine-tuning or model customization

Who You Are

IIT / Tier-1 engineering graduate

Strong problem-solving ability

Clear communicator

Systems thinker

Comfortable debating architectural trade-offs

Bias toward clean design over hacks

Able to move from whiteboard code production

What Makes This Role Exciting

Work on frontier AI architectures for enterprise grade AI implementation (beyond POCs and demos)

High ownership

Influence technical direction

Build systems that scale

• Opportunity to shape AI strategy at an early stage