Python
React.js
Amazon Web Services (AWS)
React NativeWe are looking for an Engineering Lead to own the entire technology stack — from onboarding and underwriting to disbursals, repayments, and collections — and to build the engineering function into something genuinely AI-native.
What You'll Own
● Full tech stack: backend, frontend, infrastructure, integrations, and data pipelines
● Real-time underwriting and decisioning systems
● LOS/LMS architecture — onboarding, disbursals, repayments, and collections
● Integrations with bureaus, KYC providers, account aggregators, and payment gateways
● Reconciliation systems — disbursement, repayment, and NACH reconciliation end-to-end
● AWS infrastructure: scaling, reliability, uptime, and cloud cost ownership ● Data infrastructure for the credit and risk team — feature pipelines, model serving, experiment infrastructure
● Engineering leadership: hiring, sprint planning, code reviews, and execution standards
● Compliance systems: RBI guidelines, DPDP, KYC/AML, e-NACH, e-sign
AI-Native Engineering
This is a core part of the role, not a bonus. You will build a machine-readable knowledge base of the entire codebase — architecture, data models, service contracts, coding standards, decision history — so that AI agents working on code have the context to produce accurate, consistent output. You will build skills for code review, developer onboarding, and recurring engineering workflows. You will build a code review pipeline where agents do the first pass on every pull request. The knowledge base and the skills improve over time as the team grows and the product evolves.
What We're Looking For
● 7+ years in software engineering, with at least 2 years leading teams or architecture
● Strong hands-on experience with Python, Django, and React Native
● Deep expertise in AWS and cloud-native architecture
● Experience with both SQL and NoSQL databases
● Strong understanding of distributed systems, microservices, and API design
● Experience owning reconciliation or payment flow infrastructure in a lending or payments context
● Prior experience in fintech / NBFC / digital lending — mandatory
● Strong understanding of the full loan lifecycle — mandatory
● You have used LLMs seriously as engineering tools and have strong opinions about what makes AI-assisted development produce good output versus mediocre output
Bonus: Kubernetes / Kafka, AI/ML-driven underwriting, Account Aggregator framework, e-NACH / e-Sign / Video KYC integrations
What Success Looks Like
● scales with strong uptime, performance, and reliability
● Reconciliation runs cleanly — no financial discrepancies surface late ● A new engineer joins and is writing standard, correct code within their first week
● The credit team is never blocked on an engineering dependency
● Engineering health metrics are tracked and visibly improving
● AI agents are doing the structured first pass on code reviews, and the system gets smarter over time
Shubham Vishwakarma
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Full Stack Developer - Averlon