Senior AI Platform Engineer

• Build and run core AI platform services, including gateway integrations, skills/plugins review pipelines, a curated MCP registry, and cost and observability tooling
• Configure, extend and operate the AI gateway for routing, authentication, rate limits, quotas, metadata tagging, and onboarding teams and models
• Build and operate automated validation, review gates, versioning and release workflows for skills and plugins
• Write and review skills, agents and plugins
• Run MCP server intake, security reviews, tool scoping and allowlisting; build internal MCP servers when needed
• Implement cost tagging and attribution for token and compute spend, and build dashboards and alerts
• Instrument AI services and agents with tracing, metrics and evaluations; monitor latency, errors, quality and cost per request
• Set up scoped identities and secrets for agents and automations
• Collaborate with Security teams on reviews, incident response, access scoping, audit logging and secrets rotation
• Configure model routing rules, fallbacks and load balancing across model providers
• Build golden-path templates, CLIs and documentation; support office hours and engineering workshops
• Participate in the on-call rotation, handle production incidents and create fixes and runbooks

• 5+ years in software, platform, DevOps or SRE engineering, building and running production services
• Hands-on experience with LLM APIs, including tool use, structured outputs, streaming and prompt caching
• Practical understanding of differences between LLM providers, including Anthropic Messages and OpenAI-compatible APIs
• Experience integrating or configuring an API or LLM gateway, including routing, authentication, rate limiting and tagging
• Practical experience building with AI coding agents and extension models, including skills, plugins, MCP servers and hooks
• Strong coding skills
• Experience with Docker, Kubernetes and infrastructure as code such as Terraform on a major cloud, ideally Azure
• CI/CD experience such as GitLab CI, including automated validation and review pipelines
• Experience collaborating with Security teams to implement controls, remediate findings and support security reviews
• Experience with observability tooling such as OpenTelemetry, Prometheus and Grafana
• Experience being on call for production systems

• Competitive annual salary
• Private health insurance
• Flexible benefits plan allowing part of the compensation package to be tailored to personal needs
• Annual bonus based on individual performance and company results
• Flexible working hours
• Remote work options