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 I (FDE) who is passionate about operationalizing and collaborating closely with strategic AI enterprises and high-growth startups to architect, implement, and fine-tune production infrastructure across DigitalOcean’s AI-Native Cloud.
As an AI Infrastructure Engineer within the Forward Deployed Engineering team, you sit at the intersection of deep systems engineering and high-impact customer architecture. You won't just build infrastructure in a vacuum; you will embed directly with customer engineering teams to solve complex infrastructure bottlenecks, optimize heterogeneous GPU cluster performance, and engineer mission-critical inference and training platforms.
If you thrive on squeezing maximum compute and memory throughput out of modern GPU clusters—whether optimizing NVIDIA (H100 /H200/B200/B300) or leveraging high-capacity AMD Instinct (MI300X/MI325X) hardware—and debugging low-level distributed stacks from drivers to orchestration, this is your playground.
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 DoEmbed & Execute: Act as the primary technical authority on heterogeneous AI infrastructure for high-value DigitalOcean customers, co-engineering custom GPU infrastructure solutions for their production workloads.Optimize Multi-Vendor AI Pipelines: Architect and fine-tune low-latency, high-throughput LLM serving platforms across NVIDIA CUDA Or AMD ROCm™ platforms using serving frameworks (e.g., vLLM, TensorRT-LLM, SGLang, TGI) and model execution techniques (quantization, KV caching, speculative decoding).Cluster Orchestration & SRE: Deploy, scale, and manage resilient Kubernetes clusters (DOKS/Bare Metal) tailored for compute-heavy AI workloads, utilizing tools like Ray, Slurm, and KubeFlow.Infrastructure as Code: Build scalable, repeatable blueprints using Terraform, Ansible, and Helm to automate multi-vendor GPU provisioning, high-speed networking, and storage stacks for customer deployments.Low-Level Heterogeneous Troubleshooting: Debug complex stack issues spanning host drivers (NVIDIA CUDA / AMD ROCm, HIP), container runtimes, inter-GPU communication libraries (NCCL / RCCL), high-speed interconnects (InfiniBand / RoCE / Infinity Fabric™), and distributed storage systems.Build for Scale: Translate common customer infrastructure challenges into core platform features, working directly with DigitalOcean’s product and core infrastructure teams to refine our cloud offering.Travel & Collaboration Requirements: Ability to travel up to 30% for customer engagements, strategic workshops, conferences, and internal collaboration. Ability to consistently overlap with North American business hours, including availability until at least noon Eastern Time, to collaborate effectively with customers, Product, Engineering, and go-to-market teams.
What You’ll Add to DigitalOcean- Cloud & Orchestration: Expertise with Linux systems engineering, Kubernetes, and Infrastructure as Code (Terraform, Helm).
Heterogeneous GPU & Acceleration Stack: Hands-on experience managing NVIDIA Stack (CUDA, NCCL, NVLink, and Triton Inference Server ) Or AMD Stack ( ROCm™ RCCL, CDNA™)
- Inference & Distributed AI: Experience with modern LLM serving frameworks (vLLM, TensorRT-LLM, Ray Serve) running on both CUDA and ROCm backends.
- Networking & Storage: Deep understanding of high-performance interconnects (RDMA, InfiniBand, RoCE, AMD Infinity Fabric™) and high-throughput storage systems suited for massive datasets (e.g., Ceph, Lustre, NVMe-oF).
- Programming: Strong proficiency in Python and Go (C++, CUDA C/C++, or AMD HIP is a major plus).
AI Infrastructure & Forward Deployed Engineering Experience: 6+ years of experience working in Forward Deployed Engineering, AI Infrastructure, Technical Consulting roles supporting production AI systems.
- Customer Empathy & Technical Leadership: Ability to translate complex infrastructure concepts to engineering solutions and collaborate directly with client teams (CTOs, AI Leads).
- Builder Mentality: Preference for delivering production-ready code, low-latency container images, and deployment blueprints over slide decks.
- Agility: Comfortable navigating fast-moving environments and tuning model workloads for diverse accelerator architectures.
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.
*This job is located in Bengaluru, India
JR: 2026-7937
#LI-Hybrid
- 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.
Skills Required
- Experience designing and operationalizing production AI systems including inference workloads, runtimes, orchestration, and AI-native applications
- Hands-on experience with inference/serving frameworks (vLLM, SGLang, Ray Serve, NVIDIA Dynamo, llm-d or equivalent) and LLM optimization techniques
- Deep expertise with GPU platforms and ecosystems (NVIDIA/AMD) and software: CUDA, ROCm, TensorRT, Triton, NCCL, RCCL, NVLink, XGMI, RoCE
- Strong proficiency with Kubernetes, distributed systems, networking, storage systems, and Infrastructure as Code
- Experience with AI orchestration and agent frameworks (LangGraph, CrewAI, MCP ecosystems, LlamaIndex, OpenAI Agents SDK or similar)
- Production coding skills in Python or Go and experience building tooling, automation, deployment workflows, and benchmarking frameworks
- Proven ability to benchmark and optimize AI infrastructure for scalability, reliability, latency, and workload economics
- Ability to travel up to 30% for customer engagements, workshops, and conferences
- Ability to consistently overlap with North American business hours (availability until at least noon Eastern Time)
- 4+ years in Forward Deployed Engineering, ML Engineering, Applied AI, AI Infrastructure, technical consulting, or equivalent customer-facing engineering roles
- Experience building platform enablement programs, deployment standards, or ecosystem integration strategies
- Active involvement or contributions to open-source AI/infrastructure projects
- Experience collaborating with GPU vendors, infrastructure providers, or model vendors on benchmarking and validation
DigitalOcean Compensation & Benefits Highlights
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Healthcare Strength — Health coverage is described as “market‑leading” across medical, dental, vision, and mental health, with 100% employer‑paid life and disability insurance. Wellbeing resources such as an EAP and tools like Headspace, Carrot, and Rightway are also highlighted.
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Equity Value & Accessibility — Ownership opportunities include new‑hire and performance RSU grants alongside an Employee Stock Purchase Plan offered at a discount. These elements are positioned as core components of the total‑rewards package.
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Retirement Support — Retirement programs feature a safe‑harbor 401(k) with employer match and immediate vesting, plus HSA contributions and a suite of FSAs. These offerings are presented to strengthen long‑term financial security.
DigitalOcean Insights
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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Remote Workspace
Employees work remotely.
We commit to both remote work and in-person collaboration. These ways of working are dependent on specific roles and are mutually agreed upon by employees. In the US, we are mainly remote. In our APAC locations, we have a hybrid in-office approach.
