Manager, Software Engineering
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Requirements
• 10+ years of professional software engineering experience, including ownership of large-scale backend systems in production. • 3+ years of hands-on technical leadership (as Tech Lead or Manager) with a track record of leading complex, cross-team projects while contributing to code and design. • 5+ years of experience with Golang (preferred) and/or Java, plus strong computer science fundamentals (data structures, concurrency, distributed systems). • Deep understanding of AWS cloud-native architectures and services (e.g., ECS/EKS, Lambda, OpenSearch, DynamoDB, RDS, S3) and resilience patterns. • Proficiency with microservices, API design, and event-driven systems, as well as experience with containerization and orchestration (Docker, Kubernetes). • Strong operational mindset: expert in observability, monitoring, incident response, performance engineering, and adherence to security best practices. • Familiarity with CI/CD pipelines, automated testing strategies (unit, integration, e2e), and modern DevOps workflows; comfortable with Git-based trunk/branch strategies. • Excellent communication, stakeholder management, and decision-making skills; able to clearly frame tradeoffs and drive alignment across engineering and product teams.
Responsibilities
• Architect and design scalable, resilient, high-performance backend systems and platforms in AWS, prioritizing reliability, security, and cost efficiency. • Contribute hands-on to key initiatives—including design reviews, prototyping, coding, performance tuning, and debugging—typically 30% of your time, while mentoring engineers and establishing high standards. • Lead cross-team technical initiatives; drive design forums, establish engineering guardrails, and ensure high-quality delivery via code reviews and automation. • Partner closely with Product, Design, Data Science, and Platform teams to define project scope, sequence milestones, and proactively de-risk execution for iterative releases. • Own design of APIs and microservices, including REST and event-driven patterns, and enforce best practices for versioning, contracts, and backward compatibility. • Advance operational excellence by defining SLOs, improving observability and alerting, hardening on-call procedures and runbooks, and leading incident response and post-mortems. • Solve complex distributed system challenges (such as throughput, latency, consistency, and data modeling) with pragmatic decision-making and balanced tradeoffs. • Document architectural decisions, service ownership, and operational runbooks to share knowledge and maintain long-term scalability. • Foster team growth through clear expectations, actionable feedback, and mentorship; hire, develop, and onboard diverse talent committed to a culture of ownership and collaboration.