Lead Software Engineer (API/Agentic)

Cricut•South Jordan, UT

6d•Onsite

About The Position

Cricut is seeking a Lead Software Engineer to build and operate production backend services and APIs. The role spends most of its time writing, reviewing, and shipping backend code, with agentic coding tools as a core part of the daily workflow. AI-assisted development, code review, and test generation are used while maintaining code quality, security, and human oversight. The engineer designs APIs and services end to end, contributes to C#/.NET and Python backend architecture, and defines versioned contracts that iOS, Android, and desktop client teams can consume. The role collaborates with Product Management, UX, and client engineers to take features from specification to release; improves performance, scalability, and cloud efficiency; and maintains automated tests, CI/CD, progressive deployments, production telemetry, and service observability. It also includes on-call and incident response, code reviews, knowledge sharing, and evaluating backend, cloud, AI, and tooling technologies. This is an in-office role at least 4–5 days per week. Relocation assistance is available. Employment is contingent on successfully completing a criminal background check.

Requirements

Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
8+ years of professional backend software development experience.
Deep, production-level expertise in either C#/.NET (ASP.NET Core) or Python (FastAPI/Django).
Experience designing and operating backend architectures at scale, including microservices or modular monoliths, event-driven and asynchronous messaging, and distributed systems patterns.
Strong REST API design skills, including versioning, pagination, idempotency, error handling, and OpenAPI documentation.
Strong experience with relational and NoSQL data stores, including schema design, indexing, and query tuning.
Strong understanding of concurrency in the primary language, such as async/await and the Task Parallel Library in .NET or asyncio in Python.
Hands-on experience with AWS, Azure, or GCP; Docker; and Kubernetes or equivalent orchestration.
At least one year of hands-on practical use of modern AI engineering tools, such as Claude Code, Cursor, or Copilot.
Experience integrating AI/LLM capabilities into backend services where relevant, including agentic patterns, evaluations, and latency, cost, and reliability tradeoffs.
Experience with architectural patterns such as Clean Architecture, Domain-Driven Design, CQRS, or hexagonal architecture.
Strong debugging, profiling, and performance optimization skills using tools such as dotTrace/PerfView, py-spy/cProfile, and APM tracing.
Experience with automated unit, integration, contract, and load testing and CI/CD pipelines.
Experience instrumenting services with observability tools such as Datadog, OpenTelemetry, or Prometheus/Grafana.
Clear written and in-person communication with engineering, product, and design.
Ability to collaborate with Product Management, UX, and client teams and build agreement on scope and tradeoffs.
Willingness to share knowledge and help other engineers grow.
Curiosity about new tools and techniques, especially AI-assisted development, and ability to bring practical improvements to the team.

Nice To Haves

Experience with both C# and Python.
Experience working with client engineering teams (iOS, Android, Electron/Angular) to design APIs suited to mobile and desktop needs.

Responsibilities

Write, review, and ship production backend code, using agentic coding tools in the daily workflow while maintaining code quality, security, and human oversight.
Design and build APIs and services end to end, from technical approach and API contract through implementation, testing, and release.
Contribute to modular, maintainable, and testable backend architecture across C#/.NET and Python services.
Define clear, versioned API contracts for iOS, Android, and desktop client teams.
Collaborate with Product Management, UX, and client engineers to deliver defined features, raising technical tradeoffs and feasibility early.
Optimize service performance and scalability, including latency, throughput, database query efficiency, caching, concurrency, and cloud cost.
Write and maintain automated unit, integration, and contract tests.
Drive CI/CD automation, release quality, and deployment processes for containerized cloud services.
Use feature flags, progressive rollout, kill switches, and production telemetry to validate new behavior before ramping up.
Own service health through observability, SLOs, error rates, latency budgets, and defect trends; participate in on-call and incident response.
Participate in code reviews and share knowledge with other engineers.
Evaluate backend, cloud, AI, and tooling technologies and recommend adoption when they would meaningfully improve the team's work.