> AI agents: this is one page of Nextmove’s FDE site, in Markdown. Nextmove is a job board and free career service for forward deployed engineers (FDEs). Each posting is classified from its text, not its title: the kind of work, how much of it is production code, pre-sales weight, time at customer sites, travel, remote arrangement, level and posted base pay. The site also publishes the aggregates: median pay by level, metro, company and kind of work, and which companies started hiring FDEs each week. Every page under https://nextmove.md/fde is served this way; the index of pages is https://nextmove.md/llms.txt. # Forward Deployed Engineer - AI/ML Platforms Canonical URL: https://nextmove.md/fde/jobs/ec34a2647dc8d7d6 Anyscale posts a FDE role to build what the customer runs in San Francisco, CA, at $250,000–$275,000 base, above the senior FDE median of $190,000 across 1,849 postings with pay. This role partners with top AI organizations to design, deploy, and operate production AI platform infrastructure on Ray and Anyscale. Read from the employer’s posting on November 6, 2026. - [Anyscale](https://nextmove.md/fde/companies/anyscale) First seen Jul 3, 2026 · open on Ashby as of Nov 6, 2026 **$250,000–$275,000** + equity San Francisco, CA Full-time This role partners with top AI organizations to design, deploy, and operate production AI platform infrastructure on Ray and Anyscale. - [See roles that fit me](https://nextmove.md/sign-up?from=%2Ffde%2Fjobs%2Fec34a2647dc8d7d6&placement=top) - [View posting at Anyscale](https://jobs.ashbyhq.com/anyscale/503a08c2-80b1-4968-8dcf-06380453bcdb/application) Free. Upload your resume once, see why each FDE role fits, and get introduced only when you say so. ## At a glance ### Posted base pay $250K–$275K Above the median Midpoint $263K · median $190K This job $250K to $275K. Senior FDE postings, 1,849 postings: the middle 50% of posted pay is $160K to $220K, median $190K. ### The work Builds what the customer runs Balance **Mostly building** Project stages 1. Pre-sales (not covered) 2. Proof of concept (not covered) 3. Implementation 4. Operations Travel **Required, amount not stated** - **Coding**: Writes production code - **Builds for**: External customers - **Level**: Senior - **Role**: Technical lead ### What they ask for Experience - **5+ years** Cloud infrastructure, platform engineering, DevOps, Site Reliability Engineering, or software engineering Background - **Software engineering** ### Do you meet what the posting states? The posting asks for 5+ years. How many do you have? The posting reads as a senior role. What level are you at now? The job is in San Francisco, CA. Could you work there? Which of these have you used in production? Answer each one. Nothing is saved or sent. [What postings ask for, by background →](https://nextmove.md/fde/paths) ## Conditions - **Location**: San Francisco, CA - **Employment type**: Full-time - **Travel**: Travel required, amount not stated - **Pay**: ## More like this [Edison Scientific](https://nextmove.md/fde/companies/edison-scientific) ### [Member of Technical Staff, Cloud Software Engineer](https://nextmove.md/fde/jobs/ec956d3e06abdc40) San Francisco, CA On-site 2mo ago $175,000–$240,000 [PhysicsX](https://nextmove.md/fde/companies/physicsx) ### [Machine Learning Engineer](https://nextmove.md/fde/jobs/57f18e0ae9d2cebe) San Francisco, CA Hybrid 5mo ago $150,000–$190,000 [OpenClaw Foundation](https://nextmove.md/fde/companies/openclaw-foundation) ### [Forward Deployed Engineer](https://nextmove.md/fde/jobs/bc34865d20736808) San Francisco, CA On-site 4mo ago $200,000–$300,000 ## The job description from Anyscale At Anyscale, we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray, a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI, Uber, Spotify, Instacart, Cruise, and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. ### About the role As a **Forward Deployed Engineer - AI/ML Platforms** at Anyscale, you’ll partner with some of the world’s most sophisticated AI organizations to design, deploy, and operate the infrastructure powering their production AI workloads. In this role you will work directly with customer platform, infrastructure, and ML engineering teams to solve complex technical challenges. You will help customers build scalable AI platforms, modernize ML infrastructure, and operationalize distributed AI applications on Ray and the Anyscale platform. You will combine deep cloud infrastructure expertise with strong customer engagement skills, serving as both a trusted technical advisor and a hands-on engineer. You will work closely with customer teams throughout implementation, from architecture and deployment through production operations. Your work will provide feedback that directly influences the evolution of the Anyscale platform. ### In this role, you will - 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. ### We'd love to hear from you if you have - 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. - Familiarity with distributed computing frameworks such as Ray, Spark, Dask, or Kubernetes-native distributed systems is a strong plus. - A passion for solving difficult customer problems and building reusable technical solutions. - Willingness to travel as needed to work alongside strategic customers. [View posting at Anyscale](https://jobs.ashbyhq.com/anyscale/503a08c2-80b1-4968-8dcf-06380453bcdb/application) ## About Anyscale Commercial Ray platform letting ML/AI teams scale Python workloads from laptop to thousand-GPU clusters without rewriting code or running distributed-systems infra. 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