
Principal Software Engineer - Security
DigitalOcean · Posted Nov 3
Cloud infrastructure, virtual machines, managed database, and AI inference services
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About the role
DigitalOcean is a cloud platform that aims to simplify cloud and AI for builders. The role sits in the CISO’s organization and partners with Security Data Science and Security leadership teams. The Principal Engineer, AI/ML Security will lead AI security strategy, risk and governance, adversarial testing, and threat modeling across customer-facing products and ML systems.
What you will 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
Skills used in this role
What the employer is looking for
- 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 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.
Benefits and support
- Reimbursement for relevant conferences, training, and education (subject to company policy)
- Flexible time off
- Local team meetups
- Mental health and well-being support
- Equity compensation, including potential new hire equity grant
- Employee Stock Purchase Program (in participating countries)
- Annual bonus plan
About DigitalOcean
DigitalOcean is an American cloud infrastructure provider and AI-native cloud platform built for developers, startups, and small-to-medium-sized businesses. The company provides simple, scalable virtual machines, managed databases, Kubernetes, and specialized inference engines designed to run modern application and agentic AI workloads.
- Industry
- Cloud Computing
- Company size
- 1001-5000 employees
- Founded
- 2011-06-24
- Location
- Broomfield, Colorado, USA
- Funding stage
- Public Company
Funding
Public Company · $174M raised
- 2013-07-01Seed$3.2M
- 2014-03-01Series A$37.2M
- 2014-12-01Debt Financing$50M
- 2015-07-01Series B$83M
- 2016-04-01Debt Financing$130M
- 2020-05-01Venture Round$50M
- 2021-03-24IPO$775.5M
Leadership
Chief Executive Officer
Chief Financial Officer
Chief Product and Technology Officer
Chief Marketing Officer
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