Staff Forward Deployed Engineer
DigitalOcean5 months ago
Base Salary
$195k - $239k/yr
Responsibilities
- Partner with strategic AI-native customers on complex migrations, production-ready proofs of concept, and hands-on application builds on GPU infrastructure.
- Build reusable migration planners, systems, benchmarking frameworks, model optimization agents, and deployment automation scripts using tools such as Terraform and Pulumi.
- Create GenAI agents, solution templates, and notebooks using frameworks such as LangGraph and CrewAI.
- Surface architectural gaps and edge cases to influence the product roadmap and transition field-built tools into native product features.
- Lead early testing and integration of emerging AI frameworks to improve the DigitalOcean developer experience.
- Co-develop delivery frameworks with strategic and technical partners to enable repeatable deployments.
- Produce field-tested demonstration kits and deployment guides for product releases.
- Measure and improve production workload adoption, time-to-production, pilot-to-production conversion, tooling adoption, deployment-pattern handoffs, and product influence.
Requirements
- Significant experience with the AI/ML lifecycle, including hosting large language or multimodal models with inference engines such as vLLM, SGLang, or Modular.
- Deep knowledge of LLM architectures and optimization techniques such as continuous batching and quantization.
- Expertise with NVIDIA and AMD GPU families and related software stacks, including CUDA, ROCm, TensorRT, and OpenAI Triton.
- Expert proficiency in Kubernetes and distributed systems, including microservices, messaging systems, databases, and Infrastructure as Code.
- Ability to integrate AI workloads with networking, VPC, storage, and compute cloud services.
- Hands-on experience with distributed inference serving frameworks such as llm-d, NVIDIA Dynamo, or Ray Serve.
- Understanding of GPU-level optimization and interconnect technologies such as NVLink, XGMI, and RoCE.
- Strong production coding skills in Python or Go.
- Proven ability to benchmark AI infrastructure and tune GPU utilization for workload performance and customer ROI.
- Proven ability to establish technical credibility with CTOs and lead architects while managing high-stakes migrations.
- Preferred experience with LangGraph, CrewAI, or LlamaIndex.
- Preferred background in technical consulting or Forward Deployed roles at AI or infrastructure companies.
- Preferred experience building and scaling Center of Excellence models or partner delivery frameworks.
- Active contribution to open-source AI projects or technical communities is preferred.
Benefits
- Hybrid work arrangement.
- Reimbursement for relevant conferences, training, and education.
- Access to LinkedIn Learning courses.
- Employee Assistance Program, local employee meetups, and flexible time off.
- Potential bonus, equity compensation, equity grants upon hire, and Employee Stock Purchase Program.
Tech Stack
Categories
Forward Deployed
About DigitalOcean
DigitalOcean provides cloud infrastructure and platform services for developers, startups, and small to mid-sized businesses, including virtual machines (Droplets), managed Kubernetes and databases, object/block storage, networking, and GPUs for AI workloads. It operates a usage-based, self-service public cloud with APIs, CLI, and a marketplace to deploy and scale applications. Founded in 2012 and headquartered in Broomfield, Colorado, DigitalOcean is a public company listed on the NYSE.