Role OverviewThe AI Platform Engineer will help build the modern platform capabilities that move machine learning and generative AI from experimentation into secure, reliable, and scalable production use.
What You Will Do
Engineer model and LLM deployment, inference, serving, gateway, evaluation, monitoring, registry, and lifecycle capabilities, build reusable platform services, automate environments, deployments, testing, rollback, and infrastructure using CI/CD and infrastructure-as-code.
Why It Might Be a Fit
The ideal candidate is a hands-on builder who enjoys solving complex platform problems and turning emerging technology into durable enterprise capability.
Requirements
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience
- 5+ years of ML engineering, MLOps, platform engineering, cloud engineering, DevOps, or related experience
- Strong Python and experience with containers, Kubernetes or comparable orchestration, APIs, CI/CD, infrastructure-as-code, and observability
- Experience deploying and operating machine learning or generative AI workloads in production
- Working knowledge of model serving, RAG, vector databases/search, LLM gateways and model routing, agent frameworks and tool/MCP integration, evaluation, LLM observability (traces, tokens, latency, cost per task), security, and AI workload economics
Benefits
- Medical, Dental and Vision
- 401(K)
- Employee Stock Purchase Plan
- Flex Spending Accounts
- Life & Disability Insurance
- Vacation, Sick, Personal Time and Company Holidays
- Multiple Voluntary and Company provided Benefits
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