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Forward Deployed Engineer

Job in Seattle, King County, Washington, 98113, USA
Listing for: DigitalOcean
Full Time position
Listed on 2026-05-21
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Systems Engineer
Job Description & How to Apply Below
Position: Staff Forward Deployed Engineer
Dive in and do the best work of your career rney alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you'll find your place here.

We value winning together-while learning, having fun, and making a profound difference for the dreamers and builders in the world.

We are looking for a Staff Forward Deployed Engineer who is passionate about solving complex cloud infrastructure challenges in the fast-growing AI/ML space. This is a high-impact position designed to be the "technical tip of the spear" for our most strategic AI-Native (ANE) customers.

As an FDE, you will sit at the intersection of Product Engineering and Customer Implementation. You will be embedded directly with our most strategic customers to drive transformational AI adoption. You will collaborate closely with customer teams to ship advanced AI applications that solve real world business problems.

You will build the tools, migration scripts, and AI starter kits that don't just solve one customer's problem, but scale the entire Digital Ocean AI Cloud ecosystem. Your mission is to accelerate "time-to-inference" in production at scale and serve as a critical feedback loop, ensuring our product roadmap is informed by the world's most demanding AI workloads.

What You'll do:

* Embedded Customer Engineering:
Partner deeply with strategic ANEs to manage complex migrations, build production-ready PoCs, and execute hands-on application builds on our GPU infrastructure.

* Build Scalable Assets & Tooling:
Operationalize field learning by building migration planners, reusable systems, benchmarking frameworks, model optimization agents, and deployment automation scripts (e.g., Terraform/Pulumi) that standardize how AI workloads are deployed and tuned across Digital Ocean.

* Develop AI "Starter Kits":
Create pre-built GenAI agents, solution templates, and notebooks (e.g., Lang Graph, CrewAI) tailored to popular and advanced business needs.

* Drive the Product

Roadmap:

Act as the frontline technical voice for CPTO, surfacing architectural gaps and edge cases to inform core product development. Transition field-built tools into native product features.

* New Tech Validation:
Lead the early testing and integration of emerging AI frameworks to ensure a first-class developer experience on Digital Ocean.

* Partner & GTM Enablement:
Co-develop delivery frameworks with Strategic and Technical partners to enable repeatable, high-quality deployments at scale.

* Market Leadership:
Produce field-tested demo kits and deployment guides that support new product releases with practical, validated assets.

Key Metrics

* Customer Adoption:
Number of high-impact production workloads landed; reduction in average "time-to-production"; and Pilot-to-Production conversion rates.

* Asset & Tooling Delivery:
Number of reusable tools (agents, scripts, playbooks) delivered per quarter and their subsequent adoption rate by the cross functional teams and customers.

* Field Enablement & Scale:
Measured by the successful handoff and execution of FDE-defined deployment patterns to technical partners and the internal adoption rate of FDE playbooks across all customer-facing technical teams.

* Product Influence:
Number of roadmap features or architectural changes directly attributed to FDE feedback and validated customer hypotheses.

What You'll Add to Digital Ocean:

* AI/ML Architecture & Domain Expertise:
Significant experience in the AI/ML lifecycle, specifically hosting large language or multimodal models using inference engines like vLLM, SGLang, or Modular. You have a deep understanding of common LLM architectures and optimization techniques (e.g., continuous batching, quantization).

* Distributed Systems & Infrastructure Mastery:
Act as the subject matter expert on modern GPU families (NVIDIA/AMD) and their software stacks (CUDA, ROCm, Tensor

RT, OpenAI Triton). Expert proficiency in Kubernetes (K8s) and the design of distributed systems, including microservices, messaging systems,…
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