Forward Deployed Engineer - AI/ML Platforms

The role

You will partner with AI organizations to design, deploy, and operate infrastructure for production AI workloads. You will work with customer teams to build scalable AI platforms and operationalize distributed AI applications on Ray and the Anyscale platform.

What you will do

• Design and implement production-grade AI platform architectures on Kubernetes and public cloud infrastructure.
• Partner with customer platform, infrastructure, and ML engineering teams to deploy, operate, and optimize distributed AI workloads.
• Lead implementation engagements including platform installation, networking, security, observability, scaling, upgrades, and operational readiness.
• Troubleshoot complex distributed systems issues spanning infrastructure, Kubernetes, networking, storage, and AI applications.
• Develop automation, tooling, reference implementations, and infrastructure-as-code.
• Build trusted relationships with technical leaders, platform teams, and executive stakeholders.
• Collaborate with Product and Engineering to communicate customer requirements and shape platform capabilities.
• Share best practices through technical documentation, architecture guidance, workshops, and enablement.

Required qualifications

• 5+ years of experience in cloud infrastructure, platform engineering, DevOps, Site Reliability Engineering, or software engineering.
• Experience building, deploying, or operating ML/AI platforms that support model training, inference, or large-scale data processing workloads.
• Strong expertise with Kubernetes and containerized production environments.
• Experience operating cloud infrastructure on AWS, Azure, or GCP, including networking, security, IAM, storage, and infrastructure automation.
• Experience with Infrastructure as Code and modern DevOps tooling such as Terraform, Helm, GitOps, CI/CD pipelines, or similar technologies.
• Strong software engineering skills in Python, Go, Java, or a comparable language, with experience building automation or production services.
• Experience working directly with enterprise customers in consulting, professional services, field engineering, solutions architecture, or another customer-facing engineering role.
• Excellent communication skills and the ability to work effectively with both executive and deeply technical stakeholders.
• A passion for solving difficult customer problems and building reusable technical solutions.
• Willingness to travel as needed to work alongside strategic customers.

Nice to have

• Familiarity with distributed computing frameworks such as Ray, Spark, Dask, or Kubernetes-native distributed systems

About the company

Anyscale is commercializing Ray, a popular open-source project for scalable machine learning. The company aims to democratize distributed computing for software developers.