Senior Golang Engineer - AI Product & Platforms

• Build AI-powered products from 0-1 – Engineer production-grade, business-facing AI platforms with clean, performant, and maintainable Go code from day one
• Design and build high-performance backend services – Architect and implement low-latency, high-throughput microservices in Go that operate reliably at planetary scale
• Design and build developer tools and frameworks – Create reusable libraries, SDKs, and internal tooling in Go that accelerate development across fast-paced engineering teams
• Tackle complex distributed systems challenges – Design solutions for concurrency, fault tolerance, data consistency, and service orchestration across large-scale distributed environments
• Champion engineering excellence – Drive best practices in code quality, testing strategies, CI/CD pipelines, and observability to maintain velocity without sacrificing reliability
• Mentor and elevate the team – Guide other engineers on Go idioms, system design patterns, performance optimization, and building software that scales

• Golang expertise essential
• Deep-dive Golang engineering expertise from building high-performance, large-scale production systems
• Production system builder – proven track record of architecting and building large-scale, high-availability production applications and business-facing platforms from the ground up using Go
• Advanced Go expertise – deep proficiency in Go's concurrency model (goroutines, channels, select), memory management, profiling, and performance tuning for latency-sensitive systems
• Microservices and API design – extensive experience designing, building, and maintaining RESTful and gRPC APIs with a focus on clean contracts, versioning, and backward compatibility in high-traffic production systems
• HashiCorp Vault and secrets management – experience integrating with Vault for dynamic credentials, secrets engines, and enterprise-scale secrets management within Go services
• Enterprise authentication & authorization – designing and implementing OAuth, JWT, RBAC, and complex identity systems with fine-grained access controls in business-critical applications
• Cloud-native and Kubernetes expertise – building, deploying, and operating containerized Go applications in Kubernetes, leveraging service meshes, Helm charts, and cloud-native patterns at enterprise scale
• AI/ML platform engineering – experience building backend infrastructure and APIs that serve AI/ML models, manage inference pipelines, and support LLM-powered applications at scale
• Observability and reliability engineering – implementing comprehensive logging, metrics, distributed tracing, and alerting to ensure system health and rapid incident resolution
• Database and data layer proficiency – strong experience with both SQL (PostgreSQL, MySQL) and NoSQL (Redis, MongoDB, DynamoDB) databases, including schema design, query optimization, and caching strategies
• Testing and CI/CD mastery – building robust test suites (unit, integration, end-to-end) and designing CI/CD pipelines that enable rapid, confident deployments to production

Any specific AI engineering projects utilizing LLMs that you're proud of in your application

• 27 days annual leave (plus bank holidays)
• A discretional annual performance related bonus
• Private Medical Care & Life Insurance
• Employee Assistance Program
• Pension Plan
• Paid Parental Leave
• Special discounts for employees, family, and friends