VP - Principal Engineer
Confirmed on the employer's own hiring board on Nov 13, 2026. First seen by Alion on Nov 13, 2026.
Mintifi Finserve Pvt Ltd
Role - VP - Principal Engineer Platform Engineering & Applied AI
Function - Technology - Engineering
Level - Senior leadership (VP band) - technical / individual contributor
Reports to - CTO
Location - Mumbai
Type - Full time
About Mintifi
Mintifi is one of India's leading supply chain financing platforms, financing the dealers, distributors and vendors of large corporate anchors. Our lending runs on a stack of core systems - including our Loan Origination System (LOS) and Loan Management System (LMS) - and a growing set of distributed services built to scale.
The Role
We're looking for a Principal Engineer to be one of Mintifi's deepest technical hands - a builder who sets the engineering bar through code and design, not through a management chain. You'll own the architecture and the hard technical problems across our Java-based lending platform: designing core backend services, building AI-enabled product features, driving performance and scale, and keeping a strong security posture across a regulated lending business. This is a hands-on, individual-contributor role. You'll influence architecture across teams and mentor engineers, but your primary impact is technical - the systems you design and the standards you set.
What You'll Own
Architecture & hands-on engineering - Design and build core backend services in Java across the lending platform (LOS, LMS and distributed services), owning end-to-end technical design of complex features. - Set engineering standards - clean, well-tested, maintainable code - and raise the bar through design reviews and hands-on work, contributing across the stack (including a working level of React) where it helps.
Building AI-enabled products - Bring practical, applied AI into the product - integrating modern AI services and models (e.g. LLMs and AI APIs) into lending workflows to ship genuinely AI-enabled features. This is applied AI. - Put the right engineering around AI features - evaluation, guardrails, cost and latency control, monitoring, and safe handling of sensitive data - and use AI tooling to lift the wider team's productivity.
Performance, scale & reliability - Own performance engineering: profile, tune and scale services for growing transaction volumes at low latency. - Design for reliability across distributed, microservices-based systems - fault tolerance, observability and capacity planning.
Security & cybersecurity - Keep a security-first posture: secure coding, threat modelling, data protection, secrets management and sound authentication / authorisation, as befits a regulated lender. - Bring strong cybersecurity awareness to design and reviews - including the security implications of AI features - and partner with security and QA on VAPT remediation and compliance-aligned engineering.
Cloud & data - Architect and run services on AWS, with Kubernetes, containers and CI/CD; shape data solutions on relational databases (primarily PostgreSQL) and data lake / analytical stores, with strong data modelling and query performance.
Domain & influence - Bring deep lending-domain understanding to technical decisions across origination, underwriting, disbursement, servicing and collections.
What You Bring - Expert-level Java and deep software-engineering craft, with a long track record of building production systems at scale. - Hands-on experience building AI-enabled products - integrating AI / LLM services into real applications (applied AI, not model training). - Good cybersecurity knowledge and security-engineering practice - secure coding and data protection in a regulated environment. - Strong performance engineering and systems design across microservices and distributed architectures. - Hands-on AWS experience and cloud-native delivery, plus real lending / fintech domain expertise. - A genuine builder's disposition - this is a technical IC role, not a management track.
Good to have - Depth with Kubernetes and with data solutions on PostgreSQL and data lake / analytical stores; working React and full-stack comfort. - Familiarity with AI frameworks, RAG, agents or vector stores, and with AI-assisted developer tooling. - Event-driven / streaming (e.g. Kafka), caching, and experience in RBI /