Principal Software Engineer

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 join the CISO s organization 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 to build and deploy detection strategies, guardrails, and security tooling/automations. Partner with Security Engineering to implement online and batch inference endpoints to serve in-house AI/ML models. Participate in ongoing monitoring of deployed models to detect drift, evaluate performance, and plan and implement improvements alongside model stakeholders.
• Adversarial testing / AI red teaming: lead jailbreak, prompt-injection, evasion, poisoning, and model-extraction 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:

• Overall 15+ 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 pipeli nes, model serving, continuous monitoring) made by ML engineers and data scientists.
• Hands-on experience with AI red-team and defensive toolingand 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, N…