Senior Forward Deployed Engineer (AI/ML)
DigitalOcean, LLC, San Francisco, CA, United States
Dive in and do the best work of your career at DigitalOcean. Journey 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
Senior Forward Deployed Engineer (FDE)
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 DigitalOcean AI Cloud ecosystem. Your mission is to accelerate "time‑to‑inference" 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, GPU optimization agents, and deployment automation scripts (e.g., Terraform/Pulumi) to reduce friction for the broader field organization.
Develop AI "Starter Kits":
Create pre‑built GenAI agents, solution templates, and notebooks (e.g., LangGraph, 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 DigitalOcean.
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 DigitalOcean
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, TensorRT, OpenAI Triton). Expert proficiency in Kubernetes (K8s) and the design of distributed systems, including microservices, messaging systems, databases, and Infrastructure as Code. You can seamlessly integrate AI workloads with core cloud services (Networking, VPC, Storage, Compute).
High‑Performance Inference & Hardware Optimization:
Hands‑on experience with distributed inference serving frameworks (e.g., llm‑d, NVIDIA Dynamo, or Ray Serve). You understand GPU‑level optimization and have experience with interconnect technologies like NVlink, XGMI, or RoCE to maximize hardware efficiency.
Software Engineering Foundation:
Strong production coding skills in
Python
or
Go
with the ability to build high‑quality tools, automation, and internal assets.
Data‑Driven Performance Insight:
Proven ability to benchmark AI infrastructure and perform GPU utilization tuning to optimize customer ROI and workload performance.
Consultative Execution:
Proven ability to establish instant technical credibility with CTOs and Lead Architects while managing high‑stakes technical migrations.
Preferred
Experience with emerging AI orchestration frameworks like
LangGraph, CrewAI, or LlamaIndex .
A background in technical consulting or "Forward Deployed" roles at high‑growth AI or infrastructure companies.
Experience building and scaling "Center of Excellence" models or partner delivery frameworks.
Active contributor to open‑source AI projects or technical communities.
Compensation Range
$140,000 - $174,000
Benefits
Competitive salary and bonus structure based on company and individual performance.
Equity compensation, including equity grants upon hire and Employee Stock Purchase Program participation.
Comprehensive benefits including health, dental, vision, life insurance, and a flexible time‑off policy.
Professional development opportunities such as conference reimbursement, LinkedIn Learning access, and internal training resources.
Employee assistance and wellness programs.
Strong commitment to diversity, equity, and inclusion.
DigitalOcean is an equal‑opportunity employer.
We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
#J-18808-Ljbffr
We are looking for a
Senior Forward Deployed Engineer (FDE)
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 DigitalOcean AI Cloud ecosystem. Your mission is to accelerate "time‑to‑inference" 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, GPU optimization agents, and deployment automation scripts (e.g., Terraform/Pulumi) to reduce friction for the broader field organization.
Develop AI "Starter Kits":
Create pre‑built GenAI agents, solution templates, and notebooks (e.g., LangGraph, 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 DigitalOcean.
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 DigitalOcean
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, TensorRT, OpenAI Triton). Expert proficiency in Kubernetes (K8s) and the design of distributed systems, including microservices, messaging systems, databases, and Infrastructure as Code. You can seamlessly integrate AI workloads with core cloud services (Networking, VPC, Storage, Compute).
High‑Performance Inference & Hardware Optimization:
Hands‑on experience with distributed inference serving frameworks (e.g., llm‑d, NVIDIA Dynamo, or Ray Serve). You understand GPU‑level optimization and have experience with interconnect technologies like NVlink, XGMI, or RoCE to maximize hardware efficiency.
Software Engineering Foundation:
Strong production coding skills in
Python
or
Go
with the ability to build high‑quality tools, automation, and internal assets.
Data‑Driven Performance Insight:
Proven ability to benchmark AI infrastructure and perform GPU utilization tuning to optimize customer ROI and workload performance.
Consultative Execution:
Proven ability to establish instant technical credibility with CTOs and Lead Architects while managing high‑stakes technical migrations.
Preferred
Experience with emerging AI orchestration frameworks like
LangGraph, CrewAI, or LlamaIndex .
A background in technical consulting or "Forward Deployed" roles at high‑growth AI or infrastructure companies.
Experience building and scaling "Center of Excellence" models or partner delivery frameworks.
Active contributor to open‑source AI projects or technical communities.
Compensation Range
$140,000 - $174,000
Benefits
Competitive salary and bonus structure based on company and individual performance.
Equity compensation, including equity grants upon hire and Employee Stock Purchase Program participation.
Comprehensive benefits including health, dental, vision, life insurance, and a flexible time‑off policy.
Professional development opportunities such as conference reimbursement, LinkedIn Learning access, and internal training resources.
Employee assistance and wellness programs.
Strong commitment to diversity, equity, and inclusion.
DigitalOcean is an equal‑opportunity employer.
We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
#J-18808-Ljbffr