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DigitalOcean is the Inference Cloud built for production AI.
The Role
Lead and grow a Forward Deployed Engineering team focused on internal data and AI platform pipelines. Drive customer engagements, validate and optimize AI workloads, influence product roadmap, build automation and benchmarking, collaborate with partners, and support production deployments and platform scale.
Summary Generated by Built In
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.
DigitalOcean is building the AI-Native Cloud for the next generation of AI companies. As Director of the Internal Data Platform organization, you will lead a team of highly technical engineers and data scientists responsible for DigitalOcean’s internal data pipeline.
This role operates at the intersection of product, and engineering. You will mentor and grow a team of FDEs while remaining hands-on in strategic customer engagements, platform validation, AI workload optimization, and product acceleration initiatives.
The ideal candidate combines deep AI infrastructure and agentic expertise with strong engineering leadership, thrives in ambiguity, and demonstrates a builder mentality. You are equally comfortable mentoring engineers, influencing roadmap discussions, reviewing architecture decisions, and rolling up your sleeves to help solve complex customer or platform challenges.
While this is a management role, it is not a traditional people-management position. The successful candidate will spend their time balancing team leadership, technical strategy, and hands-on problem solving to help customers and DigitalOcean succeed in the rapidly evolving AI infrastructure landscape.
Team Leadership & Growth
- Coach, mentor, and develop a team of Forward Deployed Engineers through regular feedback, career development, and technical leadership.
- Foster a culture of ownership, execution, continuous learning, and customer obsession.
Strategic Customer & Platform Execution
- Partner with strategic AI-native customers to architect, deploy, optimize, and scale production AI and agentic systems.
- Lead complex onboarding, migration, and workload expansion initiatives across DigitalOcean's AI-Native Cloud.
- Act as an escalation point for critical customer and platform challenges.
Technical Leadership & Product Acceleration
- Provide hands-on guidance for architecture, design, performance optimization, and operational best practices.
- Validate new AI platform capabilities, surface product and architectural gaps, scaling bottlenecks, and influence roadmap priorities through research and real-world customer workloads.
- Collaborate closely with Product, Engineering, Research, and ecosystem partners to accelerate platform maturity.
Automation & Operational Scale
- Drive the development of automation, benchmarking systems, deployment frameworks, operational playbooks, and reference architectures.
- Improve team scalability, execution speed, and quality-of-life through better tooling and processes.
Ecosystem Collaboration
- Partner with GPU vendors, model providers, and infrastructure partners on validation, optimization, benchmarking, and launch readiness initiatives.
Travel
- Ability to travel up to 30% for customer engagements, strategic workshops, conferences, and internal collaboration.
Key Metrics
- Team growth, retention, and technical leadership development
- Successful production deployments and AI platform adoption
- Product influence and platform improvements driven by customer insights
- Adoption of FDE-built automation, tooling, and deployment frameworks
- Improvements in team efficiency, onboarding velocity, and operational scale
Engineering Leadership
6+ years of experience leading highly technical engineering, infrastructure, consulting, or platform teams while developing senior engineers and driving execution.
AI Infrastructure Expertise
Hands-on experience with production AI systems, inference workloads, agentic applications, and serving frameworks such as vLLM, SGLang, Ray Serve, NVIDIA Dynamo, llm-d, or equivalent technologies.
Distributed Systems & Performance Engineering
Deep expertise with NVIDIA and AMD GPU ecosystems (CUDA, ROCm, NCCL, RCCL, TensorRT, Triton), Kubernetes, networking, storage, distributed systems, and AI infrastructure optimization.
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 coding skills in Python or Go and expertise in using agentic coding tools with experience building automation, deployment tooling, benchmarking systems, and operational platforms.
Builder Mentality
A first-principles thinker who operates comfortably in ambiguity, takes founder-level ownership, and is willing to jump into technical challenges to help the team succeed.
Executive Communication & Cross-Functional Execution
Ability to establish credibility with customers, engineering leaders, product teams, and ecosystem partners while driving strategic initiatives and customer outcomes.
- Experience in Forward Deployed Engineering, ML Engineer, Applied AI Engineer, AI Infrastructure, Technical Consulting, or equivalent customer-facing engineering roles.
- Experience building platform enablement programs, deployment standards, and adoption frameworks
- Open-source contributions within AI, infrastructure, or developer tooling ecosystems
- Experience collaborating with GPU vendors, model providers, or infrastructure partners on benchmarking, optimization, and launch readiness
*This job is located in Bengaluru, India
#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.
Skills Required
- 6+ years leading technical engineering, infrastructure, consulting, or platform teams
- Hands-on experience with production AI systems, inference workloads, and agentic applications
- Experience with serving frameworks such as vLLM, SGLang, Ray Serve, NVIDIA Dynamo, or llm-d
- Expertise with GPU ecosystems and tooling: CUDA, ROCm, NCCL, RCCL, TensorRT, Triton
- Expertise with Kubernetes, distributed systems, networking, storage, and AI infrastructure optimization
- Experience with AI orchestration and runtime/agent frameworks (e.g., LangGraph, CrewAI, MCP, LlamaIndex, OpenAI Agents SDK)
- Strong coding skills in Python or Go
- Experience building automation, deployment tooling, benchmarking systems, and operational platforms
- Ability to travel up to 30% for customer engagements and workshops
- Executive communication and cross-functional collaboration skills with product, engineering, and partners
- Experience in Forward Deployed Engineering, ML Engineer, Applied AI Engineer, AI Infrastructure, or technical consulting
- Experience building platform enablement programs, deployment standards, and adoption frameworks
- Open-source contributions within AI, infrastructure, or developer tooling
- Experience collaborating with GPU vendors, model providers, or infrastructure partners on benchmarking and optimization
DigitalOcean Compensation & Benefits Highlights
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Healthcare Strength — Health coverage includes medical, dental, vision, and mental-health support plus employer-paid life/AD&D/disability, with multiple plan options and above-average employer contributions. Offerings are described as market-leading and in some cases fully paid to keep premiums low.
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Equity Value & Accessibility — Equity awards (new-hire and performance RSUs) are paired with an Employee Stock Purchase Plan offered at a discount. This ownership component augments cash compensation and broadens participation in company growth.
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Parental & Family Support — Paid parental leave is provided for a defined period and includes a structured, part-time transition-back program. The approach emphasizes a smoother return-to-work experience for new parents.
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The Company
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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DigitalOcean Offices
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.
Typical time on-site:
