SDE 3 – Backend (Digital Credit Platform)

Location: India (Remote / Hybrid)

Experience: 5 to 8+ Years

Domain: Fintech, Lending, or Credit Systems

About the Role

As an SDE 3 (Backend), you will be the driving force behind the execution of our core platform transformation. Working closely with our Staff Engineers, you will translate our architectural blueprint into reality—moving our Digital Credit Application away from a legacy monolith and into a pluggable, high-performance API ecosystem.

This role is tailored for a highly technical, hands-on lead engineer who loves writing elegant Low-Level Designs (LLD), building high-throughput services from scratch, and enforcing world-class coding standards.

The AI Edge: We don't just tolerate AI coding tools; we expect you to master them. As an SDE 3, you will lead by example using AI Software Development Lifecycle (AI DLC) tools (such as Cursor, GitHub Copilot, or LLM agents) to bypass boilerplate code, refactor complex legacy flows into clean Java, and build automated testing suites at a high velocity.

Core Responsibilities

Feature Ownership & System Design

• High & Low-Level Design: Take active ownership of both High-Level Design (HLD) refinement and complex Low-Level Design (LLD) for modern, distributed microservices.

• Monolith Decoupling: Execute the core coding, refactoring, and data-migration tasks required to break business logic out of the legacy monolith into autonomous services.

• Pluggable Architecture: Implement clean interfaces and dynamic routing engines that allow the business to seamlessly inject or swap out credit rules and third-party data APIs.

Performance & API Engineering

• High Throughput / Low Latency: Write highly optimized, asynchronous, and thread-safe backend code capable of scaling across millions of credit requests.

• Contract-First APIs: Build and maintain clean REST/gRPC endpoints using OpenAPI specs, ensuring seamless consumption by frontend, mobile, and AI Chat clients.

• Event-Driven Resilience: Implement Kafka/RabbitMQ messaging patterns to ensure eventual consistency, handling complex transaction states via patterns like Saga or Event Sourcing.

AI DLC Integration & Execution

• AI-Augmented Development: Be the internal champion for AI-assisted engineering. Use advanced AI prompt/context engineering to generate clean code, catch edge-case bugs, and draft bulletproof contract tests.

• Test Automation: Maintain high code coverage by integrating automated unit, integration, and performance testing into our CI/CD pipelines.

Technical Leadership

• Mentorship: Conduct rigorous, constructive code reviews and mentor SDE 1 and SDE 2 engineers in clean code principles (SOLID).

• Operational Excellence: Own the telemetry of your services—baking in OpenTelemetry, Prometheus alerts, and Grafana tracking from day one.

Key Qualifications

Technical Competency & Stack

• 5 to 8+ Years of Backend Experience: Proven track record of shipping production-grade systems, ideally within Fintech, Lending, Neobanking, or Payments.

• Expert Java Stack: Deep, hands-on experience with Java 17/21, Spring Boot 3.x, and Spring Cloud.

• Distributed Databases: Proficiency in relational databases (PostgreSQL/MySQL) and NoSQL stores (MongoDB/DynamoDB), including advanced schema design, indexing, and query optimization.

• Message Brokers: Strong experience with asynchronous event messaging using Kafka or RabbitMQ.

• Rules Engines & Workflows: Familiarity with workflow orchestration tools or rules frameworks (e.g., Camunda, Drools, or JSON-logic configurations) is a massive plus.

Modern Workflows & AI

• AI DLC Proficiency: Regular use of AI code-generation and refactoring tools to optimize development workflows and speed up delivery times.

• Cloud Infrastructure: Strong familiarity with cloud ecosystems (AWS preferred) and container orchestration tools (Docker, Kubernetes).

Education & Soft Skills

• Strong algorithmic thinking, data structures, and cross-functional problem-solving skills.

• Excellent communication skills—able to break down complex code topologies for product teams.

• Bachelor’s degree in Computer Science, Information Technology, or a related field.