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Forward Deployment Engineer Jobs in Seattle, WA (NOW HIRING)

Speechify

Go-to-Market - Tacoma, WA, USA

Tacoma, WA · On-site

$150K - $200K/yr

Prior experience in a forward deployment or solutions engineering capacity * Multilingual or experience selling into international markets Why Speechify SIMBA * Sell a product that genuinely ...

Istari Digital

Forward Deployed Engineer

Seattle, WA · On-site

$143K - $165K/yr

As a Forward Deployed Engineer, you'll be embedded directly inside our customer organizations ... Write clean, maintainable code that can be productized or reused across customer deployments

Speechify

Go-to-Market - Seattle, WA, USA

Seattle, WA · On-site

$150K - $200K/yr

Prior experience in a forward deployment or solutions engineering capacity * Multilingual or experience selling into international markets Why Speechify SIMBA * Sell a product that genuinely ...

Istari Digital

Forward Deployed Engineer

Seattle, WA · On-site

$143K - $165K/yr

As a Forward Deployed Engineer, you'll be embedded directly inside our customer organizations ... Write clean, maintainable code that can be productized or reused across customer deployments

Istari Digital

Forward Deployed Engineer

Seattle, WA · On-site

$143K - $165K/yr

As a Forward Deployed Engineer, you'll be embedded directly inside our customer organizations ... Write clean, maintainable code that can be productized or reused across customer deployments

Speechify

Go-to-Market - Redmond, WA, USA

Redmond, WA · On-site

$150K - $200K/yr

Prior experience in a forward deployment or solutions engineering capacity * Multilingual or experience selling into international markets Why Speechify SIMBA * Sell a product that genuinely ...

Tari Labs, LLC.

Forward Deployed Engineer

Seattle, WA · On-site

$143 - $165/hr

As a Forward Deployed Engineer, you'll be embedded directly inside our customer organizations ... Write clean, maintainable code that can be productized or reused across customer deployments

Istari Digital

Forward Deployed Engineer

Seattle, WA

$143K - $165K/yr

As a Forward Deployed Engineer, you'll be embedded directly inside our customer organizations ... Write clean, maintainable code that can be productized or reused across customer deployments

Speechify

Go-to-Market - Seattle, WA, USA

Seattle, WA · On-site

$150K - $200K/yr

Prior experience in a forward deployment or solutions engineering capacity * Multilingual or experience selling into international markets Why Speechify SIMBA * Sell a product that genuinely ...

3M HEALTHCARE

Staff Forward Deployed Engineer

Seattle, WA · On-site

$195 - $239/hr

We are looking for a Staff Forward Deployed Engineer who is passionate about solving complex cloud ... Produce field‑tested demo kits and deployment guides that support new product releases with ...

OpenAI

Forward Deployed Engineer (FDE) - Seattle

Seattle, WA · On-site

$162K - $280K/yr

About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping ...

Talkdesk

Senior Forward Deployed Engineer, FSI

Seattle, WA · On-site

$180K - $225K/yr

The Senior Forward Deployed Engineer, FSI (FDE) is a high impact technical leader responsible for ... You own the technical execution for deployments, mitigate technical risks, and drive successful ...

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All JobsForward Deployment Engineer JobsForward Deployment Engineer Jobs in Seattle, WA

Forward Deployment Engineer information

See Seattle, WA salary details

$40.4K

$124.7K

$193.5K

How much do forward deployment engineer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for forward deployment engineer in Seattle, WA is $124,683.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,600.00 and $157,600.00 per year, depending on experience, location, and employer.

What is a forward deployment engineer?

Forward Deployment Engineers (FDEs) are technical professionals who work directly with clients to implement, customize, and deploy software solutions. They act as a bridge between engineering teams and customers, ensuring that products are successfully integrated into the client's environment and tailored to meet their specific needs. FDEs typically handle a mix of software engineering, problem-solving, and client-facing responsibilities, often traveling to customer sites to provide on-the-ground support. Their role is essential for organizations that offer complex technical products requiring hands-on deployment and adaptation.

What are the key skills and qualifications needed to thrive as a forward deployment engineer?

To thrive as a Forward Deployment Engineer, you need strong analytical and problem-solving skills, a solid foundation in computer science or engineering, and relevant experience or a degree in these fields. Familiarity with programming languages (such as Python or Java), cloud platforms, and deployment/configuration management tools is typically required, along with knowledge of client-facing software solutions. Outstanding communication, adaptability, and teamwork skills help you understand client needs and collaborate effectively across teams. These skills ensure successful implementation and integration of complex software solutions in diverse client environments.

How does a forward deployment engineer typically collaborate with clients and internal teams during a project?

Forward Deployment Engineers often serve as a bridge between clients and internal engineering or product teams. They work closely with clients to understand their unique requirements, configure solutions, and ensure successful deployments, frequently traveling to client sites. Internally, they collaborate with engineers, product managers, and support staff to relay client feedback, troubleshoot issues, and optimize system performance. This role requires excellent communication skills and adaptability, as each project may involve different stakeholders and technical challenges.

What is the difference between Forward Deployment Engineer vs Network Engineer?

AspectForward Deployment EngineerNetwork Engineer
Required CredentialsBachelor's in CS, EE, or related; certifications like CCNA, Cisco, or cloud certificationsBachelor's in CS, EE, or related; certifications like CCNA, CompTIA Network+
Work EnvironmentOn-site deployments, fieldwork, client sites, and data centersOffice-based, network infrastructure setup, maintenance, and troubleshooting
Industry UsageTech, telecom, cloud providers, hardware vendorsIT, telecom, enterprise networks, service providers

While both roles require networking knowledge and certifications like CCNA, Forward Deployment Engineers focus on deploying and supporting hardware and systems directly at client sites, often involving fieldwork. Network Engineers primarily design, implement, and maintain network infrastructure within organizations. The roles overlap in certifications and industry usage but differ in work environment and deployment focus.

What do forward deployment engineers do?

Forward deployment engineers are responsible for deploying, maintaining, and troubleshooting hardware and software systems at client sites or in the field. They often work closely with customers to ensure systems operate effectively and may require skills in networking, scripting, and technical support. Their role involves on-site presence, rapid problem resolution, and ensuring operational readiness of deployed solutions.

What are popular job titles related to Forward Deployment Engineer jobs in Seattle, WA?

For Forward Deployment Engineer jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Forward Deployment Engineer jobs in Seattle, WA look for?

The top searched job categories for Forward Deployment Engineer jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Forward Deployment Engineer jobs?

Cities near Seattle, WA with the most Forward Deployment Engineer job openings:

Forward Deployment Engineer jobs near you
Infographic showing various Forward Deployment Engineer job openings in Seattle, WA as of August 2026, with employment types broken down into 2% Internship, 88% Full Time, and 10% Contract. Highlights an 73% In-person, 7% Hybrid, and 20% Remote job distribution, with an average salary of $124,683 per year, or $59.9 per hour.

Staff Forward Deployed Engineer, AI/ML

DigitalOcean

Seattle, WA • On-site

Full-time

Re-posted 16 days ago

Job description

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 Staff Forward Deployed Engineer (FDE) who is passionate about operationalizing production AI-native and agentic workloads at scale. This is a high-impact role designed to serve as the "technical tip of the spear" for DigitalOcean's most strategic AI-native customers and platform initiatives.
As an FDE, you will operate at the intersection of Product Engineering, AI Infrastructure, and Customer Implementation. You will partner deeply with strategic AI-native enterprises (ANEs), startups, infrastructure vendors, and internal engineering teams to deploy, optimize, and scale production AI systems on DigitalOcean's AI-Native Cloud.
This role extends beyond traditional GPU infrastructure deployment. You will work across Inference Engine, runtime systems, orchestration frameworks, and AI-native applications to help customers operationalize production AI and agentic systems with strong focus on scalability, reliability, latency, and workload economics.
FDE engineers also act as the "first customer" for new AI-native platform capabilities. You will validate products under real-world workloads, surface operational insights and architectural gaps, and help accelerate product maturity through continuous feedback loops with Product Engineering and Research teams.
You will build scalable deployment frameworks, benchmarking systems, automation tooling, and AI starter kits that transform field learning into reusable platform intelligence and repeatable deployment patterns across the DigitalOcean ecosystem.
Your mission is to accelerate production adoption of AI-native systems while helping shape the future of DigitalOcean's AI-Native Cloud for the inference and agentic era.
What You'll Do
  • Strategic AI Workload Operationalization: Partner with strategic ANEs and AI startups to architect, deploy, optimize, and scale production AI and agentic systems on DigitalOcean's AI-Native Cloud. Support complex migrations, production-ready PoCs, deployment acceleration, and long-term workload expansion across inference and runtime platforms.
  • AI Performance & Systems Engineering: Optimize distributed inference and runtime performance through benchmarking, GPU efficiency tuning, KV-cache optimization, speculative decoding, prefill/decode disaggregation, multi-node deployments, and latency/cost optimization.
  • Platform Validation & Product Acceleration: Act as the "first customer" for DigitalOcean's AI-native platform capabilities including Inference Engine, runtimes, orchestration systems, GPU platforms, and deployment workflows. Surface real-world operational insights, architectural gaps, and scaling bottlenecks directly to Product Engineering and Research teams.
  • Platform Intelligence & Automation: Build scalable deployment assets including benchmarking systems, automation tooling, AI starter kits, deployment frameworks, operational playbooks, finetuning workflows, and reference architectures that improve deployment velocity and platform adoption.
  • Ecosystem & Technical Enablement: Collaborate with GPU vendors, model providers, infrastructure partners, and ISVs on co-development, technical validation, optimization, and launch readiness. Enable customer-facing technical teams and partner teams through validated deployment patterns, benchmarking insights, operational playbooks, reference architectures, demos, and technical guidance that help scale adoption of DigitalOcean's AI-native platform.
  • Travel: Ability to travel up to 30% for customer engagements, strategic onsite workshops, ecosystem partnerships, conferences, and internal collaboration.
Key Metrics
  • Customer Adoption & Production Success: Measured by high-impact production workloads launched, reduction in time-to-production, pilot-to-production conversion rates, and expansion of AI-native platform adoption across strategic customers.
  • Platform Intelligence & Product Influence: Measured by product improvements, roadmap influence, validated customer hypotheses, and operational insights generated from real-world production deployments.
  • Asset & Tooling Delivery: Measured through adoption of FDE-built frameworks, automation tooling, benchmarking systems, operational playbooks, and reference architectures across customers and internal teams.
  • Field Enablement & Ecosystem Scale: Measured through successful enablement of customer-facing teams, ecosystem collaboration outcomes, and adoption of FDE deployment standards across the AI-native ecosystem.
What You'll Add to DigitalOcean
  • AI-Native Systems & Architecture Expertise: Experience designing and operationalizing production AI systems including inference workloads, agentic runtimes, orchestration frameworks, and AI-native applications. Strong hands-on experience with inference and serving frameworks such as vLLM, SGLang, Ray Serve, NVIDIA Dynamo, llm-d, or equivalent systems, along with LLM optimization techniques including continuous batching, quantization, KV-cache optimization, and speculative decoding.
  • Distributed Systems & Infrastructure Mastery: Deep expertise with NVIDIA and AMD GPU platforms and their software ecosystems including CUDA, ROCm, TensorRT, Triton, NCCL, RCCL, NVLink, XGMI, and RoCE. Strong proficiency with Kubernetes (K8s), distributed systems, networking, storage systems, Infrastructure as Code, and large-scale AI infrastructure architectures.
  • Runtime & Orchestration Systems: Experience with AI orchestration and agent frameworks such as LangGraph, CrewAI, MCP ecosystems, LlamaIndex, OpenAI Agents SDK, or similar runtime systems. Understanding of workflow orchestration, deployment systems, memory patterns, and AI-native application architectures.
  • Software Engineering & Automation: Strong production coding skills in Python or Go with experience building tooling, automation systems, deployment workflows, benchmarking frameworks, and operational platforms.
  • Performance & Operational Intelligence: Proven ability to benchmark and optimize AI infrastructure with strong focus on scalability, reliability, GPU efficiency, runtime performance, latency optimization, and workload economics.
  • Consultative & Cross-Functional Execution: Ability to establish technical credibility with CTOs, Principal architects, Product Engineering teams, and ecosystem partners while managing high-impact production deployments and strategic technical initiatives.
Preferred Qualifications
  • AI Infrastructure & Forward Deployed Engineering Experience: Experience working in Forward Deployed Engineering, AI Infrastructure, Technical Consulting, AI Platform Engineering, or equivalent customer-facing engineering roles supporting production AI systems.
  • Platform Enablement & Ecosystem Experience: Experience building deployment standards, technical enablement programs, platform adoption frameworks, or ecosystem integration strategies across customer-facing and engineering organizations.
  • Open Source & AI Ecosystem Involvement: Active contributor to open-source AI, infrastructure, orchestration, or developer tooling ecosystems.
  • Vendor & Strategic Partnership Collaboration: Experience collaborating with GPU vendors, infrastructure providers, model vendors, or ecosystem partners on benchmarking, optimization, technical validation, or launch readiness initiatives.
Compensation Range:
  • $220,000 - $239,000

*This is a hybrid role
JR: 2026-7748
#LI-Hybrid
Why You'll Like Working for DigitalOcean
  • We innovate with purpose. You'll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions.
  • We prioritize career development. At DO, you'll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development.
  • We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences.
  • We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.
  • 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.

Application Limit: You may apply to a maximum of 3 positions within any 180-day period. This policy promotes better role-candidate matching and encourages thoughtful applications where your qualifications align most strongly.

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