Staff Backend Engineer

Responsibilities

• Architect and build high-throughput backend services that process real-time operational data.
• Lead technical design reviews and choose pragmatic approaches for new features and system improvements.
• Design event-driven and distributed systems that are resilient, observable, and performance-tuned.
• Define stable APIs for internal and external consumers, partnering with frontend for seamless integration.
• Improve engineering excellence through code reviews, standards, testing strategy, and incident practices.
• Build and maintain CI/CD workflows that enable rapid, secure delivery.
• Troubleshoot complex production issues, lead incident response, and drive durable fixes.
• Partner with product and operational stakeholders to translate needs into deliverable technical plans.
• Contribute to technical strategy and roadmap planning across backend services.
• Support hiring by participating in interviews and helping define what “great” looks like.

Requirements

Must Have

• 10+ years building scalable backend systems in production environments.
• 4+ years of experience in Golang, or 4+ years writing server-side business logic in an object-oriented language (Java, Kotlin, C#, Python) or systems language (C, C++, Rust) with strong system design aptitude.
• Led technical initiatives end-to-end, including architecture, execution, and delivery.
• Experience designing distributed systems (e.g., event-driven architectures, messaging, consistency tradeoffs).
• Built cloud-native services and operated them in production (AWS preferred).
• Strong security fundamentals: secure coding, threat modeling, and defensible design choices.
• Track record mentoring engineers through code reviews, technical guidance, and feedback.
• Strong communication skills and can align teams around clear technical decisions.

Nice To Have

• Experience designing data models and queries in graph databases (e.g., Neo4j, AWS Neptune).
• Used relational databases (Postgres, MySQL, MariaDB) to solve business problems and reason about query performance.
• Worked on defense, intelligence, or security-focused products with real operational users.
• Shipped large-scale data processing systems (streaming, near-real-time analytics, or similar).
• Integrated ML/AI capabilities into production systems in a practical, measurable way.
• Open-source contributions or personal projects that demonstrate strong engineering craft.

Tech Environment

• Go (Golang) business logic
• AWS and hybrid cloud/on-prem deployments
• Event-driven messaging (e.g., NATS)
• Containers and orchestration (Docker, Kubernetes)
• GraphQL and service-to-service APIs
• Graph databases (Neo4j, AWS Neptune) and complex relationship data