Lead Engineer

ABOUT YUBI

Yubi (formerly CredAvenue) is redefining global debt markets by freeing the flow of finance between borrowers, lenders, and investors — the world's possibility platform for the discovery, investment, fulfilment, and collection of any debt solution. In March 2022, we became India's fastest fintech unicorn with a $137M Series B. Our platforms — Yubi Credit Marketplace, Yubi Invest, Financial Services Platform, Spocto, and Corpository — serve 17,000+ enterprises and 6,200+ investors, facilitating over ₹1,40,000 crore in debt volumes. Backed by Insight Partners, Sequoia Capital, Dragoneer, B Capital, LightSpeed, and Lightrock.

ROLE OVERVIEW

As a Lead Engineer (Agentic AI) at Yubi, you will architect and deliver production-grade intelligent systems that redefine how debt capital flows between borrowers, lenders, and investors. You will lead a pod of engineers, own the technical roadmap for key AI agent capabilities, and work hand-in-hand with Product and Data Science to bring ambitious ideas to life at scale. This role demands deep full-stack expertise across Java, a strong grasp of LLM orchestration, and the leadership instinct to elevate the entire team around you.

KEY RESPONSIBILITIES

Technical Leadership & Architecture

• Own the end-to-end architecture of multi-agent systems — from LLM reasoning layers to React dashboards, Python, and Java microservices.
• Define technical standards, design patterns, and coding practices for the AI platform engineering pod.
• Lead design reviews, ensuring systems are scalable, secure, observable, and maintainable.
• Evaluate emerging AI frameworks and tools; make adoption decisions that balance innovation with production reliability.
• Drive migration of rule-based financial workflows to LLM-native agentic pipelines.

Agentic AI Engineering

• Architect multi-agent orchestration using LangGraph, AutoGen, or CrewAI — supporting tool use, memory, planning, and reflection loops.
• Design stateful agent memory systems combining short-term context windows with long-term vector stores for financial workflows.
• Build reliable prompt engineering strategies with versioning, A/B testing, and rollback capabilities.
• Implement compliance-aware guardrails: PII masking, hallucination detection, regulatory disclosure injection.
• Oversee RAG pipeline design — chunking strategies, embedding model selection, retrieval optimisation, and re-ranking.

People & Delivery

• Lead, mentor, and grow a team of 3–6 engineers; conduct regular 1:1s, code reviews, and career development conversations.
• Drive sprint planning, estimation, and delivery commitments in close partnership with the Product Manager.
• Participate in senior technical hiring — define interview criteria and assess engineering bar.

REQUIRED SKILLS & QUALIFICATIONS

Technical

• 5–8 years of full-stack engineering experience, with at least 1-2 years in AI/LLM product development.
• Very strong problem solving capability . Doing HLD and LLD for a given problem
• Good understanding of data structures , algorithms
• Good Understanding of CI/CD pipelines and test driven development
• Proven experience building production LLM-powered products — prompt engineering, agent orchestration, output validation.
• Hands-on with LangChain, LangGraph, AutoGen, or equivalent agent frameworks.
• Strong understanding of RAG, vector search, and embedding-based retrieval.
• Experience with Kafka or similar message brokers; familiarity with event-driven architecture patterns.
• Kubernetes, Docker, and cloud-native AWS experience at production scale.

Leadership & Soft Skills

• Proven track record of leading engineering teams and delivering complex projects end-to-end.
• Excellent communication — able to translate AI system behaviour to product, business, and compliance stakeholders.
• Strong systems thinker with the ability to decompose complex financial workflows into reliable automated steps.
• B.E. / B.Tech / M.Tech in Computer Science or equivalent; advanced degree a plus.