Staff Software Engineer

Responsibilities:

• Architecture and System Design: Design and evolve the architecture of the connector platform to support thousands of integrations while maintaining scalability, performance, and reliability.
• Hands-on Engineering: Write production-grade code, implement complex technical solutions, and contribute directly to critical components of the platform.
• Distributed Systems: Design and troubleshoot distributed systems handling high-throughput data processing, concurrent workloads, and complex failure scenarios.
• Connector Development: Build and optimize integrations across SaaS applications, databases, streaming platforms, files, and APIs.
• Data Processing: Work with data formats such as JSON, Parquet, and Avro, ensuring efficient processing at scale.
• Performance and Scalability: Identify bottlenecks and optimize system performance, resource utilization, throughput, and latency.
• Reliability Engineering: Improve fault tolerance, retry mechanisms, error handling, observability, and production reliability across the connector ecosystem.
• API Development: Design and implement robust APIs using REST and gRPC to support seamless communication between platform components.
• Infrastructure and Deployment: Build and optimize services running on Kubernetes, ensuring reliable operation under high-throughput workloads.
• Technical Ownership: Independently drive complex engineering initiatives from design through implementation, deployment, and production monitoring.
• Cross-functional Collaboration: Work closely with backend, API, UI, and product teams to translate business requirements into scalable technical solutions.
• Code Quality and Technical Excellence: Conduct design and code reviews, establish engineering best practices, and improve existing systems through continuous technical innovation.
• AI-assisted Engineering: Leverage AI-powered development tools to improve engineering productivity while applying sound technical judgment to validate their outputs.

Requirements:

• Experience: 8-12 years of experience building and scaling backend systems in production environments.
• Strong JVM Expertise: Deep hands-on experience with Java or other JVM-based technologies and the ability to troubleshoot complex production issues.
• Distributed Systems: Strong understanding of distributed architectures, concurrency, fault tolerance, and high-throughput systems.
• Kafka: Production experience building or operating Kafka-based systems at scale.
• Caching Technologies: Hands-on experience with Redis or Memcached.
• API Technologies: Strong experience designing and developing REST and gRPC APIs.
• Kubernetes: Experience deploying, operating, and optimizing backend services on Kubernetes, particularly under high-throughput workloads.
• Scalable Backend Architecture: Demonstrated experience designing systems for high availability, performance, and reliability.
• Production Debugging: Ability to diagnose complex system failures, performance bottlenecks, and issues spanning multiple services.
• Hands-on Technical Ownership: Proven ability to independently own critical systems, make architectural decisions, and deliver complex technical solutions.
• AI Development Tools: Practical experience using AI coding assistants and the ability to evaluate their strengths and limitations.