Position Overview
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.
What You'll Do
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
What You'll Add to DigitalOcean
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.
Preferred Qualifications
- 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
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