Director, AI Engineering
@ DigitalOcean

Boston, Massachusetts, United States
$240,000
On Site
Full Time
Posted 4 hours ago

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Job Details

About DigitalOcean

Dive in and do the best work of your career at DigitalOcean. Join a high-caliber community of talent, driving simplicity in scalable cloud solutions.

Role Overview

As the Director, AI Engineering at DigitalOcean, you will lead AI product engineering efforts, bridging platform infrastructure with applied AI to deliver developer-friendly tools and integrations that simplify building intelligent applications.

What You’ll Be Doing

  • Lead technical strategy and execution for AI features.
  • Build and scale teams developing ML-powered tools and APIs.
  • Collaborate with product, data science, and design teams.
  • Ensure high standards for security, performance, and reliability.
  • Monitor industry trends for emerging AI/ML opportunities.
  • Foster a culture of ownership and technical excellence.

What We Expect

  • 12+ years in software engineering with 5+ years in leadership.
  • Proven track record in delivering AI/ML-enabled products.
  • Deep expertise in machine learning systems, infrastructure, and cloud-native architecture.
  • Strong communication skills to align cross-functional teams.
  • Experience in mentoring and growing high-performing teams.
  • Bachelor’s or Master’s degree in a relevant field.

Why DigitalOcean?

At DigitalOcean, you will be part of a forward-thinking tech company redefining cloud simplicity. Enjoy career development resources, competitive benefits, equity compensation, and a culture that values diversity and inclusion.

Key Skills/Competency

  • AI Engineering
  • Machine Learning
  • Cloud-Native
  • Technical Leadership
  • Scalable Architectures
  • Developer Tools
  • Team Building
  • Product Collaboration
  • Security
  • Innovation
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How to Get Hired at DigitalOcean

🎯 Tips for Getting Hired

  • Research DigitalOcean's culture: Understand their mission and values.
  • Customize your resume: Highlight AI and leadership experience.
  • Showcase technical expertise: Emphasize cloud-native and ML projects.
  • Prepare for interviews: Review product and team collaboration examples.

📝 Interview Preparation Advice

Technical Preparation

Review cloud-native architecture fundamentals.
Study scalable ML system design patterns.
Update on AI/ML industry trends.
Practice API and integration development.

Behavioral Questions

Describe a time leading a diverse team.
Explain your conflict resolution approach.
Discuss handling high-pressure project deadlines.
Detail a previous innovation challenge.

Frequently Asked Questions