Job Description :

Software Development Engineer II (SDE-II) Backend / Java

3+ years experience

About the role :

We build the backend that moves people.

Our platform plans routes, allocates cabs and vendors, tracks live trips, and reconciles trip sheets at scale a fleet of Spring Boot microservices talking over Kafka and backed by PostgreSQL, serving real-world logistics where both correctness and latency matter.

As an SDE-II you'll own services end to end and operate them in production. The core of the job is system design taking ambiguous, large-scale problems (routing, allocation, distance/ETA, scheduling) and turning them into systems that are reliable, resilient, and built to scale.

You'll set the technical direction for the components you own, raise the bar through code review, and mentor engineers earlier in their journey. This is a fast-paced environment short iteration cycles, real production ownership, and priorities that shift as the business moves.

You'll need to ship high-quality work quickly, make sound calls with incomplete information, and balance speed against the long-term health of the systems you own.

You'll also work on a team where AI is a first-class part of how we design, write, and review code. We expect you to be genuinely fluent with these tools not just curious about them.

What you'll be doing :

1. Design systems, not just services :

Own the high-level and low-level design for your area service boundaries, data models, API contracts, and the event flows that connect them. Make and defend the trade-offs (consistency vs. availability, sync vs. async, build vs. reuse).

2. Build for scale :

Design features that hold up as traffic, data, and the fleet grow partitioning, caching, asynchronous processing, and back-pressure where they're needed, and simplicity everywhere else.

3. Engineer for resilience and reliability :

Build services that degrade gracefully: timeouts, retries with backoff, circuit breakers, idempotency, and dead-letter handling. Define SLOs, instrument for them, and own the result in production.

4. Drive event-driven architecture :

Design Kafka-based flows with clear ownership of delivery semantics, ordering, and failure recovery.

5. Own data design :

Model and evolve PostgreSQL schemas for correctness and performance; reason about indexing, query plans, transactions, and safe online migrations.

6. Operate what you build :

Set up metrics, structured logging, tracing, and alerting; lead debugging of live issues and drive incidents to root cause and prevention.

7. Raise the bar in code review :

Review pull requests with rigor, mentor junior engineers, and improve the standards and patterns the team builds on.

8. Use AI tools well :

Apply AI coding/review tools across the workflow to move faster while staying fully accountable for the quality and correctness of what ships.

9. Partner across functions :

Work with product and other engineering teams to scope problems, break them into shippable increments, and deliver them with honest estimates and clear communication.

What we're looking for (must-have) :

- 3+ years designing, building, and operating production backend systems.

- A track record of system design at scale you can take an open-ended problem to a clear architecture and explain why, covering availability, consistency, failure modes, and growth.

- Strong Java fundamentals concurrency, the JVM, and writing code that's correct under load plus deep, hands-on Spring Boot / Spring experience.

- PostgreSQL (or strong relational DB) expertise: schema design, query tuning, transactions, and safe migrations.

- Production experience with Apache Kafka or a comparable streaming/messaging system, including how to make event pipelines reliable.

- Experience designing REST APIs and building in a microservices architecture, with a real sense for resilience patterns and observability.

- Hands-on experience using AI development tools (Claude / Claude Code, GitHub Copilot, or similar) in day-to-day engineering, with good judgment about where they help.

- A daily code-review practice and the maturity to both give and receive feedback well.

- Clear communication and the ability to drive work to completion independently.

- Thrives in a fast-paced environment ships quickly without cutting corners, and stays effective when priorities shift.

Skills that set you apart (nice-to-have) :

- Designing for high availability and high throughput load testing, capacity planning, latency/cost trade-offs.

- Distributed systems depth: consistency models, distributed locking, eventual consistency, exactly-once vs. at-least-once.

- Observability at scale: Prometheus/Grafana, distributed tracing, SLO-based alerting.

- Cloud and infra: Docker, Kubernetes, CI/CD, AWS/GCP/Azure.

- Performance engineering profiling, JVM tuning, query and cache optimization.

- Caching / in-memory data (Redis), search (Elasticsearch), or reactive stacks.

- Domain exposure to logistics, routing, geospatial, scheduling, or marketplace/allocation systems.

- Experience shaping AI-assisted engineering workflows for a team.

- Mentoring engineers and contributing to architecture or design review forums.