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Jitterbit is a leading Integration Platform as a Service (iPaaS) company that automates critical business processes and data workflows for enterprises. The engineering team is distributed, performance-oriented, and deeply committed to code quality and technical excellence.
As a Java Backend Software Engineer, you will design, architect, and implement robust, scalable distributed systems powering Jitterbit's SaaS platform. This is a senior individual contributor role with significant technical depth and mentorship responsibilities.
Key Responsibilities:
- Design and implement high-performance, fault-tolerant connector integrations and adapters handling mission-critical business workflows 24/7/365
- Architect distributed microservices following cloud-native design patterns (circuit breakers, bulkheads, observability) for multi-tenant SaaS environments
- Build and optimize data pipelines supporting multiple protocols (REST, SOAP, GraphQL, gRPC, webhooks) and communication patterns (synchronous, asynchronous, event-driven)
- Drive technical decisions on critical subsystems; contribute to RFCs and architectural reviews; mentor junior engineers on system design principles
- Implement comprehensive monitoring, logging, and tracing; own operational health and observability of deployed systems
- Collaborate with Product, DevOps, and SRE teams to deliver features, resolve production incidents, and improve platform reliability
- Champion best practices including code reviews, testing strategies (unit, integration, chaos), security hardening, and performance optimization
- Contribute to platform infrastructure and developer experience initiatives benefiting the entire engineering organization
Team Culture:
The team values quality-first mindset, distributed ownership (engineers own subsystems end-to-end), active mentorship culture, and constant innovation. The company is very distributed with a culture optimized for remote effectiveness.
Requirements:
- Strong experience designing and building large-scale, distributed backend systems handling high throughput and low latency
- Production experience with multi-tenant SaaS architectures; deep understanding of isolation, rate-limiting, and resource management across tenants
- Proven ability to drive system design and participate in architectural decisions; experience mentoring engineers on design patterns and best practices
- Strong problem-solving and debugging skills; demonstrated ability to diagnose complex production issues in distributed systems
- Deep experience with microservices architecture, including service decomposition, API design, and inter-service communication patterns
- Hands-on experience with cloud platforms (AWS, Google Cloud, or Azure); familiarity with container orchestration (Kubernetes) and serverless patterns
- Strong foundation in software engineering fundamentals: SOLID principles, design patterns, system design, testing strategies (unit, integration, e2e)
- Expert-level Java (Java 8+): Strong OOP principles, concurrency, performance tuning, memory management (heap, GC), and Java ecosystem (Spring Boot, Guava, Netty, etc.)
- Protocol expertise: REST, SOAP, GraphQL, gRPC, and related concepts (HTTP semantics, caching, rate limiting, error handling)
- Message brokers and event streaming: Hands-on experience with RabbitMQ, Apache Kafka, AWS SQS/SNS, or similar; understanding of at-least-once delivery, dead-letter queues, and stream processing
- Database technologies: Strong SQL (query optimization, indexing); experience with NoSQL databases (MongoDB, DynamoDB, Cassandra) and their consistency trade-offs
- Containerization and orchestration: Proficiency with Docker; practical production experience with Kubernetes or container runtimes
- Advanced Git workflows (branching strategies, rebasing, cherry-picking); experience with GitHub or similar platforms
- CI/CD and DevOps: Working knowledge of GitHub Actions, Jenkins, ArgoCD, or similar; ability to write build pipelines, deployment scripts, and infrastructure-as-code (Terraform, CloudFormation)
- Comfortable with Linux command line; understanding of OS-level concepts (memory allocation, processes, file systems, networking)
- Experience with observability tools: logging (ELK, Splunk), metrics (Prometheus, Grafana), and distributed tracing (Jaeger, Zipkin)
