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

1️⃣ 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

2️⃣ 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

3️⃣ 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