Why This Job is Featured on The SaaS Jobs
This Senior Software Engineer role sits at the intersection of SaaS platform engineering and applied AI, focused on production-grade agentic workflows rather than prototypes. The remit spans backend services and orchestration layers that connect LLMs to internal systems and external data sources, which is increasingly central to how SaaS products are adding automation while maintaining reliability. The company context points to a scaled fintech platform with multiple products, suggesting real-world constraints around auditability, latency, and operational risk.
From a SaaS career perspective, the work maps closely to modern platform patterns: building APIs, deploying cloud services, instrumenting observability, and designing guardrails for non-deterministic systems. Experience with RAG, tool use, and human-in-the-loop checkpoints is broadly transferable across SaaS categories where AI features must be measurable, testable, and supportable over time. Ownership across build, test, and deployment also reinforces end-to-end product engineering habits that matter in subscription software.
This role is best suited to engineers who enjoy turning ambiguous AI capabilities into dependable services, and who prefer disciplined engineering practices alongside experimentation. It fits someone comfortable making architectural tradeoffs, collaborating through reviews, and maintaining quality standards in systems that must be explainable and monitored in production.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
About Us
Yubi stands for ubiquitous. But Yubi will also stand for transparency, collaboration, and the power of possibility.
From being a disruptor in India’s debt market to marching towards global corporate markets from one product to one holistic product suite with seven products
Yubi is the place to unleash potential. Freedom, not fear. Avenues, not roadblocks. Opportunity, not obstacles.
Job Description
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 Senior Software Engineer on Yubi's Agentic AI team, you will build and deploy intelligent agents that automate complex debt-market workflows — from credit underwriting to collections orchestration. You will own features end-to-end: writing Java backend services, and wiring LLM-powered reasoning chains that turn financial processes into reliable, auditable pipelines. You will contribute to architecture decisions, mentor peers, and help raise the bar for engineering quality across the team.
KEY RESPONSIBILITIES
Agentic AI Development
Build multi-step AI agent pipelines using LangChain, LangGraph, or custom orchestration to automate lending and compliance workflows.
Implement tool-use and function-calling layers connecting LLMs to internal APIs, bureau data, GST, and MCA sources.
Design and maintain RAG pipelines with vector databases (Pinecone, pgvector, Weaviate) for document intelligence and semantic search.
Write reliable prompt pipelines with structured output parsing, retry logic, and guardrails for production robustness.
Build human-in-the-loop checkpoints — approval gates, anomaly escalation, and audit trails — for high-stakes decisions.
Quality & Collaboration
Write deterministic tests for non-deterministic agent behaviour using golden datasets and regression suites.
Participate actively in code reviews, architectural discussions, and Agile ceremonies.
Instrument agents with observability tooling (LangSmith, Datadog) to monitor token usage, latency, and failure modes.
Containerise and deploy services on AWS using Docker and CI/CD via GitHub Actions.
Requirements
REQUIRED SKILLS & QUALIFICATIONS
Technical
3–5 years of full-stack engineering experience in production environments.
Solid Core Java fundamentals — OOP principles, collections framework, multithreading, and exception handling.
Proficiency in Spring Boot for building scalable REST APIs and microservices.
Hands-on experience integrating LLM APIs: OpenAI, Anthropic, Gemini, or open-source equivalents.
Working knowledge of agent frameworks — LangChain, LangGraph, AutoGen, or similar.
Familiarity with vector databases and RAG pipeline design.
Experience with PostgreSQL, Redis, and cloud-native AWS services (Lambda, S3, ECS).
Comfortable with Docker and CI/CD pipelines.
