Golang Software Engineer

This is a high-impact engineering role requiring independent execution, technical leadership, and cross-functional collaboration in ambiguous problem spaces. Responsibilities Design and implement production-grade backend features using Go in a microservices-style architecture Build and maintain provider integration frameworks for external LLM vendors (OpenAI, Anthropic, cloud AI services) Own backend service quality through robust unit and integration testing; continuously improve CI/CD quality gates Improve data access reliability and performance across PostgreSQL and Redis Collaborate cross-functionally on architecture, scalability, security, and operational excellence Lead technical design discussions and deliver solutions independently end-to-end Work with product teams on API requirements, troubleshoot issues, and identify new requirements Contribute to platform roadmap through technical input on feasibility, trade-offs, and system design Requirements 7+ years of professional

software engineering experience with strong backend ownership Deep expertise in Go, including idiomatic design, interfaces, concurrency, context management, and error handling Hands-on experience building HTTP APIs, middleware, and service-oriented architectures Strong experience with PostgreSQL - schema design, query optimization, and database migration workflows Practical experience with Redis - caching strategies, counters, and distributed rate-limiting patterns Experience designing or working with authorization and policy systems (RBAC/ABAC concepts) Strong testing discipline in Go (table-driven tests, mocks, integration tests, and test containers) Experience operating production systems with observability tooling (OpenTelemetry metrics and tracing, dashboards, and alerting) Solid experience with Kubernetes and Helm deployments Strong CI/CD experience (GitHub Actions or equivalent) Demonstrated ability to lead technical design and execute independently Familiarity with GenAI concepts and OpenAI APIs, with a drive for self-learning Familiarity with AI-assisted development while maintaining strong quality and architectural standards Good communication and collaboration skills B2+ English level (written and verbal) Nice to have Experience building LLM gateways, API gateways, or multi-provider AI/ML integration platforms Experience with gRPC, cloud SDKs, or service integrations on AWS, Azure, or Google Cloud Platform Familiarity with API platform security controls - API keys, OIDC, secrets management, and abuse prevention Exposure to cost and performance optimization for high-volume inference or request-processing workloads Experience contributing to platform roadmap planning (epics, user stories, backlog prioritization) Background working with UX/product teams during early-stage platform definition