Architect, build, and maintain scalable backend services in Python and Go
Design resilient APIs, optimize data pipelines, and improve system performance and reliability
Own and evolve parts of our cloud infrastructure, including environment configuration and access patterns
Implement and manage infrastructure as code (Terraform or equivalent)
Design and maintain containerized services using Docker and modern deployment workflows
Integrate and test data from third-party APIs, including LLM providers like OpenAI and Anthropic
Manage performance, cost, and observability across AI integrations and backend systems
Debug and troubleshoot issues across application and infrastructure layers
Simplify and scale complex systems to support product growth and increasing data volume
Influence long-term technical direction and backend architecture
Mentor junior engineers through code reviews and coaching
Collaborate across the stack to ship product features quickly and reliably
Requirements
7+ years building and owning resilient, high-performance backend systems for user-facing or B2B products
Strong software engineering discipline
you design testable systems, write meaningful automated tests, and protect against regressions as systems evolve
Deep proficiency in Python (or similar) and a track record of designing distributed systems
Operated production workloads in cloud environments (GCP, AWS, Azure, or similar), including IAM, service accounts, access controls, and environment isolation
Improved the performance and reliability of ambiguous or legacy systems by simplifying architecture and reducing operational risk
Built and maintained infrastructure as code using Terraform or equivalent
Designed and deployed containerized services using Docker and modern CI/CD workflows
Designed scalable data models and worked deeply with databases such as MongoDB or similar
Integrated and operated third-party APIs at scale with attention to performance, cost, and failure handling
Worked with observability tooling to monitor, debug, and improve production systems
Strong communication skills and the ability to influence technical direction
Actively leverage LLMs or AI tooling to improve engineering workflows.
Must be able to work in our Seattle or NYC office 3 days per week (hybrid model)