Job description

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 Principal Engineer, AI/ML Security who is passionate about securing AI systems and operationalizing ML-powered security at cloud scale. In this role, you will report to the VP, Deputy CISO and partner closely with Security Data Science and Security leadership teams. You will lead DigitalOcean’s engagement with the external AI security community and serve as our internal expert and escalation point for all AI-related security risk. What You’ll Do: Partner with Product Security and Engineering leadership to define how AI security controls are integrated into DigitalOcean’s customer-facing products. Partner with Security Data Science and Security Engineering to build, deploy, and serve in-house AI/ML models, guardrails, tooling, and automations. Participate in ongoing monitoring of deployed models to detect drift, evaluate performance, and plan and implement improvements alongside model stakeholders. Lead adversarial testing and AI red teaming, including jailbreaking, prompt-injection, evasion, and poisoning testing. Lead security reviews of major AI product initiatives from design through launch, providing architectural sign-off and escalation guidance for high-risk decisions. Threat modeling across the AI lifecycle: data ingestion, training/fine-tuning, evaluation, model serving, RAG, agent frameworks, and post-deployment monitoring Own and drive DigitalOcean’s AI Security strategy and multi-year roadmap, defining where we invest, what risks we prioritize, and how AI security evolves as the threat landscape and product portfolio change. Architect and lead the AI Risk & Governance framework: establishing policies, standards, and controls for the responsible development, deployment, and monitoring of AI/ML systems across DigitalOcean and Cloudways. Represent AI security at executive and board-level briefings; communicate risk posture, program progress, and strategic decisions to the CISO and senior leadership in clear, business-contextualised terms. Define DigitalOcean’s position on emerging AI security topics including agentic AI, model supply chain risk, synthetic data integrity, and AI-enabled social engineering. What You’ll Add to DigitalOcean: 10+ years of experience in cybersecurity, with at least 4–5 years focused on AI/ML security, adversarial machine learning, or security data science in a production cloud or technology environment. Demonstrated track record of defining and driving AI or security programs at an organizational level — not just executing within them. You have owned a strategy, not just implemented one. Deep, practitioner-level knowledge of adversarial ML attack and defence: evasion, poisoning, model extraction, membership inference, and prompt injection at both conceptual and implementation depth. Ability to read, evaluate, and synthesise academic AI security research and translate it into concrete engineering guidance and organizational policy. Experience engaging executive and senior leadership audiences on technical risk: you can translate complex AI threat scenarios into business-level impact and justify investment decisions accordingly. Strong programming skills in Python and Go with a track record of building security tooling and automation, not just reviewing others' code. You can stand up adversarial testing, detection, and guardrail capabilities yourself. Proficiency reviewing and critiquing AI/ML system architecture (data ingestion, feature engineering, training pipelines, model serving, continuous monitoring) made by ML engineers and data scientists. Hands-on experience with AI red-team and defensive tooling and with model supply-chain frameworks. Bachelor’s or Master’s degree in Computer Science, Information Security, Mathematics, or a related field — or equivalent depth of practical experience. Fluency in OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, ISO/IEC 42001, and the EU AI Act. Prior experience in a cloud provider, security product company, or large-scale internet platform where AI/ML systems operate at significant customer-facing scale. Familiarity with LLM security in production: securing RAG pipelines, agentic frameworks, and model APIs against prompt injection, jailbreaking, and data exfiltration. Compensation Range: $230,400 - $288,000 Non-sales roles : In addition to base salary, this role is eligible to participate in DigitalOcean’s annual bonus plan and may be eligible for a new hire equity grant, subject to plan terms and local eligibility. Bonus amounts depend on company and individual performance. Sales roles (sales compensation eligible) : In addition to base salary, this role may be eligible to earn incentive compensation under the applicable sales compensation plan and may be eligible for a new hire equity grant, subject to plan terms and local eligibility. *This is a remote role JR: 2026-7824 #LI-Remote Why You’ll Like Working for DigitalOcean We innovate with purpose. You’ll be a part of a cutting-edge technology company with a high-growth trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As part of our team, you’ll embody our "Shark" mindset: bold, ambitious, and scrappy. You'll lead with a bias for action and take true ownership of our products, customer success, and team culture. We prioritize career development. At DigitalOcean, you’ll do the best work of your career. You will join a community of exceptional talent, collaborating closely with some of the brightest and most interesting people in the industry. We are a high-performance and fast-paced organization that will always challenge you to think big. Our talent development team prioritizes your professional development and provides resources to support your growth. We provide employees with reimbursement for relevant conferences, training, and education, subject to company policy. We care about your well-being. We take a comprehensive approach to our total rewards packages because we know different things drive different people. Our benefits are designed to support you and may include flexible time off, local team meetups, and mental health and well being support. Our benefits philosophy is consistent globally, but specific benefits and eligibility vary by location to reflect local needs and regulations. We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. Eligible employees may also receive equity compensation, which may include a new hire equity grant and, in participating countries, the opportunity to participate in our Employee Stock Purchase Program. Equity awards are subject to approval and the terms of the applicable plan. Non-sales roles : In addition to base salary, this role is eligible to participate in DigitalOcean’s annual bonus plan and may be eligible for a new hire equity grant, subject to plan terms and local eligibility. Bonus amounts depend on company and individual performance. Sales roles (sales compensation eligible) : In addition to base salary, this role may be eligible to earn incentive compensation under the applicable sales compensation plan and may be eligible for a new hire equity grant, subject to plan terms and local eligibility. DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, sex, disability, protected veteran status, or any other characteristic protected by applicable law. 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.

Requirements

Must-haves

Partner with Product Security and Engineering leadership to define how AI security controls are integrated into DigitalOcean’s customer-facing products.
Lead adversarial testing and AI red teaming, including jailbreaking, prompt-injection, evasion, and poisoning testing.
Lead security reviews of major AI product initiatives from design through launch, providing architectural sign-off and escalation guidance for high-risk decisions.
Threat modeling across the AI lifecycle: data ingestion, training/fine-tuning, evaluation, model serving, RAG, agent frameworks, and post-deployment monitoring
Own and drive DigitalOcean’s AI Security strategy and multi-year roadmap, defining where we invest, what risks we prioritize, and how AI security evolves as the threat landscape and product portfolio change.
Architect and lead the AI Risk & Governance framework: establishing policies, standards, and controls for the responsible development, deployment, and monitoring of AI/ML systems across DigitalOcean and Cloudways.
Represent AI security at executive and board-level briefings; communicate risk posture, program progress, and strategic decisions to the CISO and senior leadership in clear, business-contextualised terms.
Define DigitalOcean’s position on emerging AI security topics including agentic AI, model supply chain risk, synthetic data integrity, and AI-enabled social engineering.
10+ years of experience in cybersecurity, with at least 4–5 years focused on AI/ML security, adversarial machine learning, or security data science in a production cloud or technology environment.
Demonstrated track record of defining and driving AI or security programs at an organizational level — not just executing within them. You have owned a strategy, not just implemented one.
Deep, practitioner-level knowledge of adversarial ML attack and defence: evasion, poisoning, model extraction, membership inference, and prompt injection at both conceptual and implementation depth.
Ability to read, evaluate, and synthesise academic AI security research and translate it into concrete engineering guidance and organizational policy.
Experience engaging executive and senior leadership audiences on technical risk: you can translate complex AI threat scenarios into business-level impact and justify investment decisions accordingly.
Proficiency reviewing and critiquing AI/ML system architecture (data ingestion, feature engineering, training pipelines, model serving, continuous monitoring) made by ML engineers and data scientists.
Hands-on experience with AI red-team and defensive tooling and with model supply-chain frameworks.
Bachelor’s or Master’s degree in Computer Science, Information Security, Mathematics, or a related field — or equivalent depth of practical experience.
Fluency in OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, ISO/IEC 42001, and the EU AI Act.
Prior experience in a cloud provider, security product company, or large-scale internet platform where AI/ML systems operate at significant customer-facing scale.
Familiarity with LLM security in production: securing RAG pipelines, agentic frameworks, and model APIs against prompt injection, jailbreaking, and data exfiltration.
$230,400 - $288,000
This is a remote role
#LI-Remote Why You’ll Like Working for DigitalOcean
DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, sex, disability, protected veteran status, or any other characteristic protected by applicable law.

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aimlmachine learningpythongollm

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Benefits

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Pto

Professional Development