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 Senior Forward Deployed Engineer, who is passionate about helping customers evaluate, deploy, and scale AI workloads on DigitalOcean
As a Senior Forward Deployed Engineer II at DigitalOcean, you will join a dynamic team dedicated to revolutionizing cloud computing and AI. This role will be part of our pre-sales engagement motion, working directly with strategic customers, Sales, Product, and Engineering to help customers validate DigitalOcean for production AI workloads.
You will be a hands-on technical partner for customers evaluating DigitalOcean’s AI products, helping with inference engine optimization, configuration and performance tuning, POCs, benchmarks, endpoint optimization, and production-readiness planning. The ideal person will become a trusted technical advisor to strategic AI customers and a key field voice helping shape DigitalOcean’s inference roadmap, product feedback loop, and customer adoption strategy.
What You’ll Do:
- Lead strategic pre-sales AI engagements: Partner with Sales to help customers evaluate DigitalOcean for production AI workloads, including serverless inference, dedicated inference, model deployment, and GPU-backed infrastructure.
- Optimize inference engines: Select, configure, and optimize inference engines based on hardware, model architecture, workload profile, latency requirements, and throughput targets.
- Drive POCs and benchmarks: Develop configuration updates and technical approaches to win critical POCs, improve benchmark outcomes, and accelerate customer validation.
- Tune production deployments: Optimize endpoint configurations, KV cache behavior, batching strategy, speculative decoding, tensor parallelism, quantization, GPU utilization, latency, throughput, and cost efficiency.
- Support customer architecture decisions: Help customers design scalable AI architectures across inference endpoints, Kubernetes, networking, observability, storage, and production deployment patterns.
- Remove technical blockers: Act as a hands-on technical partner during strategic customer evaluations, debugging issues, reviewing configurations, building prototypes, and helping customers move from evaluation to production.
- Scale field knowledge: Build reusable architectures, playbooks, demos, reference implementations, and technical guidance that help the broader organization support AI customers more effectively.
Key Metrics:
- Strategic AI POC Win Rate: Percentage of FDE-supported AI POCs, benchmarks, or technical evaluations that convert to closed-won or approved production deployment.
- Time to Technical Validation: Reduction in time required for customers to validate serverless inference, dedicated inference, or GPU-backed workloads.
- Inference Optimization Impact: Measurable improvement in latency, throughput, GPU utilization, reliability, or cost efficiency across customer deployments.
- Product & Platform Feedback Impact: Number of high-quality customer requirements, platform gaps, or roadmap inputs surfaced from strategic engagements that lead to product improvements, fixes, or prioritized roadmap items.
What You’ll Add to DigitalOcean:
- Experience: 5+ years in a technical role focused on AI infrastructure, inference systems, open-source LLM deployment, or model optimization.
- Inference Engine Depth: Hands-on expertise with inference engines such as vLLM, TensorRT-LLM, or SGLang, with the ability to debug and resolve performance issues.
- Inference Optimization: Strong knowledge of KV cache tuning, speculative decoding, tensor/pipeline parallelism, batching, and quantization.
- Post-Training Knowledge: Experience with fine-tuning or post-training workflows such as LoRA, SFT, DPO, RLHF, or GRPO.
- Model Landscape Awareness: Strong understanding of open-source models and how to select the right model based on use case, hardware, and performance goals.
- Coding Proficiency: Strong Python skills and comfort working in production environments.
Compensation Range:
- Base: $167,200 - $209,000
*This is a remote role
JR: 2026-7695
#LI-Remote
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.