Founding AI Platform Engineer (MLOps / Backend)

Responsibilities

• Build and maintain the infrastructure and tooling used to train, evaluate, deploy, and monitor ML models and GenAI services
• Own production services, APIs, and pipelines that power recommendations, agent workflows, and customer-facing integrations
• Improve CI/CD, testing, release workflows, rollback processes, and environment management
• Establish observability across service health, model behaviour, agent quality, latency, cost, and failure modes
• Build reproducibility and lifecycle practices for models, prompts, datasets, configurations, and releases
• Support experimentation and measurement infrastructure so product and ML changes can be evaluated cleanly
• Improve reliability, scalability, security, performance, and cost efficiency across the stack
• Troubleshoot production issues end-to-end and turn recurring pain points into durable engineering improvements
• Help define the platform and engineering standards the company will rely on as it grows.
• Shipping a model or GenAI change to production becomes faster, safer, and less manual

Languages

Required

• Experience with backend services, cloud infrastructure, CI/CD, testing, observability, and automation
• Strong Python skills and comfort working across services, tooling, infrastructure, and operational workflows
• Ability to collaborate closely with ML and product teams and move ambiguous work to completion

Nice to have

• High ownership, attention to detail, and a bias toward simplifying and strengthening systems.
• Experience with MLOps workflows for model training, evaluation, deployment, and monitoring
• Experience serving ML models or LLM applications in production
• Experience with experimentation platforms, event pipelines, analytics instrumentation, or feature delivery platforms

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