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
- 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, 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.
*This job is located in Bengaluru, India
JR: 2026-7825
#LI-Hybrid
- We innovate with purpose. You’ll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions.
- We prioritize career development. At DO, you’ll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development.
- We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences.
- We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.
- DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
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.
Skills Required
- 15+ years of cybersecurity experience
- 4–5 years focused on AI/ML security, adversarial machine learning, or security data science in a production cloud or technology environment
- Experience defining and driving AI or security programs at an organizational level
- Practitioner-level knowledge of adversarial ML attacks and defenses, including evasion, poisoning, model extraction, membership inference, and prompt injection
- Ability to evaluate AI security research and translate it into engineering guidance and organizational policy
- Experience communicating technical risk to executives and senior leadership
- Strong programming skills in Python and Go, including building security tooling and automation
- Experience reviewing AI/ML system architecture across ingestion, training, serving, and monitoring
- Hands-on experience with AI red-team, defensive, and model supply-chain tooling
- Bachelor’s or Master’s degree in Computer Science, Information Security, Mathematics, or related field, or equivalent practical experience
- Fluency in OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, ISO/IEC 42001, and EU AI Act
- Experience at a cloud provider, security product company, or large-scale internet platform
- Familiarity with production LLM security, including RAG pipelines, agentic frameworks, model APIs, prompt injection, jailbreaking, and data exfiltration
DigitalOcean Compensation & Benefits Highlights
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Healthcare Strength — Health coverage is described as market‑leading across medical, dental, vision, and mental health, with above‑average employer contributions and 100% employer‑paid life, AD&D, and disability insurance. Some materials note fully paid health benefits for employees in certain locations, though details vary by region.
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Equity Value & Accessibility — Employees are offered company equity alongside an Employee Stock Purchase Plan (ESPP) that enables discounted share purchases, with references to performance equity grants as part of total rewards. This ownership component complements competitive cash pay and bonuses highlighted in company materials.
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Parental & Family Support — Parental benefits are positioned as above‑average, with references to fully paid parental leave (e.g., 10 weeks in newer listings) and a part‑time transition‑back program. Fertility and parenthood support such as Carrot is also called out.
DigitalOcean Insights
What We Do
DigitalOcean is the Inference Cloud — a full-stack, production-ready cloud platform built to run AI applications with predictable performance, sustainable economics, and radically simpler operations at scale. We are built for teams turning AI into real products — not just training models. Our advantage is not fewer features, but fewer failure modes when operating AI at scale — combining minimal operational overhead, predictable cost efficiency, and a full-stack cloud that works as a system. Hyperscalers are broad by design. Neoclouds are infrastructure-first. DigitalOcean is inference-first — with a real cloud underneath. It combines inference-optimized compute, managed inference software, and integrated cloud capabilities that reduce operational burden for teams running real workloads. Inference is the foundation—not the boundary. Everything else builds on top of it.
Why Work With Us
At DO, we do career-defining work. We innovate with AI and build cutting-edge tech. Our rewards to match that intensity - to motivate you, recognize your impact, and give you what you need to thrive. If you have a growth mindset, like to think big and bold, and are energized by the fast-paced environment, you'll find your place here.
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Employees engage in a combination of remote and on-site work.
We commit to both remote work and in-person collaboration. These ways of working are dependent on specific roles and are mutually agreed upon by employees. In the US, we are mainly remote. In our APAC locations, we have a hybrid in-office approach.
