Principal Software Engineer

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.