Forward Deployed Engineer

Responsibilities

• Design and implement production-grade AI platform architectures on Kubernetes and public cloud infrastructure (AWS, Azure, and GCP).
• Partner directly with customer platform, infrastructure, and ML engineering teams to deploy, operate, and optimize distributed AI workloads.
• Lead implementation engagements that include 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 that accelerate customer success and improve repeatability.
• Build trusted relationships with technical leaders, platform teams, and executive stakeholders, translating business objectives into robust technical solutions.
• Collaborate closely with Product and Engineering to communicate customer requirements, identify product improvements, and shape future platform capabilities.
• Share best practices through technical documentation, architecture guidance, workshops, and enablement.

Requirements

• 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.
• Willingness to travel as needed to work alongside strategic customers.

Nice-to-Haves

• Familiarity with distributed computing frameworks such as Ray, Spark, Dask, or Kubernetes-native distributed systems.
• A passion for solving difficult customer problems and building reusable technical solutions.