Senior Forward Deployed Engineer II

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.

• Base: $167200 - $209000

*This is a remote role

JR: 2026-7695

#LI-Remote

What We Do

DigitalOcean is the Inference Cloud — a full-stack production-ready cloud platform built to run AI applications with predictable performance sustainable economics and radically simpler operations at scale. We are built for teams turning AI into real products — not just training models. Our advantage is not fewer features but fewer failure modes when operating AI at scale — combining minimal operational overhead predictable cost efficiency and a full-stack cloud that works as a system. Hyperscalers are broad by design. Neoclouds are infrastructure-first. DigitalOcean is inference-first — with a real cloud underneath. It combines inference-optimized compute managed inference software and integrated cloud capabilities that reduce operational burden for teams running real workloads. Inference is the foundation—not the boundary. Everything else builds on top of it.

Why Work With Us

At DO we do career-defining work. We innovate with AI and build cutting-edge tech. Our rewards to match that intensity - to motivate you recognize your impact and give you what you need to thrive. If you have a growth mindset like to think big and bold and are energized by the fast-paced environment you'll find your place here.

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