Agentic AI and MCP - Technical Lead

Company Description

Nu10 is a New York–headquartered 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: 4–8 years

Location: In Office, Indiranagar, Bengaluru

Reports to: CTO / Head of Engineering

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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.

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What You'll 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

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Core Responsibilities

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

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

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

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Technical Requirements

Must-Have

• 4–8 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

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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

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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