Distributed Systems Engineer (High-Throughput Ledger & Sync)

About Us & Our Mission :

Our company builds mission-critical B2B SaaS architecture operating at the demanding intersection of global supply chain logistics and high-throughput fintech settlement rails. Our platform ingests millions of inventory telemetry events, transactional ledger movements, and vector search queries every single hour. Maintaining absolute data consistency, partition tolerance, and low latency across distributed nodes is the core engineering challenge that keeps our platform running smoothly.

We believe that building resilient distributed systems requires deep architectural discipline, rigorous concurrency control, and clean, modular code. If you are passionate about solving hard problems in distributed consistency, event sourcing, and high-concurrency database states, you will find your ultimate engineering home with us.

The Role & Impact :

We are seeking an elite, hands-on Distributed Systems Engineer to take full ownership of our core ledger synchronization and transactional state replication engine. In this role, you will design, build, and scale distributed backend services that guarantee ACID compliance and high availability across multi-region cloud deployments. You won't just write standard CRUD endpoints; you will architect fault-tolerant consensus mechanisms, optimize network partition recovery, and ensure that our financial ledgers and supply chain telemetry remain perfectly synchronized under massive enterprise load.

Key Responsibilities :

- Distributed Architecture : Design, build, and scale low-latency distributed microservices and consensus-driven backend architectures using Go, Rust, or Python.

- State Synchronization : Implement event-sourcing patterns, CQRS, and distributed locking mechanisms to handle high-concurrency transactional updates.

- Database Partitioning & Sharding : Architect and manage horizontal database sharding, cross-region replication, and eventual-consistency models for large-scale enterprise data stores.

- Resiliency & Fault Tolerance : Build robust retry logic, circuit breakers, dead-letter queues, and automated failover systems to handle network partitions and service degradation gracefully.

- Performance Profiling : Conduct deep bottleneck analysis, memory profiling, and network payload optimization to achieve sub-millisecond internal response times.

- Cross-Functional Collaboration : Partner closely with data engineering, DevOps, and product squads to align distributed system capabilities with evolving business requirements.

What We Are Looking For :

- Experience : 3 to 6 years of professional backend software engineering experience focusing heavily on distributed systems, concurrency, and high-throughput data processing.

- Technical Mastery : Deep proficiency in systems programming or backend engineering using Go, Rust, or Python, combined with advanced understanding of networking protocols (TCP/UDP, gRPC, HTTP/2).

- Database & Messaging Expertise : Hands-on experience with distributed databases (CockroachDB, Cassandra, or distributed PostgreSQL setups) and event streaming brokers (Apache Kafka, RabbitMQ).

- Theoretical Foundation : Solid grasp of the CAP theorem, consensus algorithms (Raft/Paxos), distributed transactions (2PC/Saga patterns), and vector clock synchronization.

- Engineering Mindset : Strong system design capabilities, meticulous debugging skills, and a proactive ownership mentality.

What We Offer :

- Competitive Compensation : Industry-leading salary package (22 - 38 LPA) structured with base pay, performance bonuses, and meaningful equity participation.

- Cutting-Edge Tech Stack : Total freedom to work with modern distributed computing primitives and high-scale enterprise architecture.

- Growth & Wellness : Comprehensive health insurance coverage for you and your dependents, plus an annual learning stipend for tech conferences and advanced training.