Staff Security Software Engineer

DigitalOcean • Denver, CO

77d • $166,400 - $208,000

About The Position

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 Staff Fraud Analyst who is passionate about hunting and minimizing fraud in the Cloud. As a Staff Fraud Analyst at DigitalOcean, you will join a dynamic team dedicated to revolutionizing cloud computing and AI. This role reports to the Senior Manager of Security Engineering within the Security organization. You should have experience hunting fraud in a complex, high-scale environment, writing and communicating consumable insights to stakeholders across the business, and devising and implementing fraud mitigations that are aligned with overall business goals. You will be working at the intersection of fraud and business imperatives like customer conversion and resource allowance, maintaining high levels of trust, and revenue collection. With a massive funnel and diverse customer base, small tweaks can have outsized impact-we'll rely on you to surface bold, data-informed strategies and decisions to protect and grow our platform.

Requirements

• 8+ years of hands-on experience in fraud analysis, risk operations, or abuse prevention, preferably in a high-scale SaaS, IaaS, or fintech environment.
• Deep familiarity with fraud tactics, including fake signups, payment fraud, bot networks, promo abuse, and Cloud infrastructure abuse.
• Strong analytical and investigation skills, with proficiency in SQL, data warehouse querying (e.g., Snowflake, Redshift, BigQuery) and ETL, and pattern recognition in high-volume datasets.
• Comfort working in complex software environments-you understand system behaviors, account and resource provisioning flows, and how they can be exploited.
• Understanding of cloud-native services and infrastructure provisioning (e.g. compute, storage, networking).
• A customer-first mindset-you aim to maximize fraud prevention while minimizing impact to high-value customers.
• Excellent communication and documentation skills; you can clearly articulate patterns, mitigation strategies, and tradeoffs to both technical and non-technical stakeholders.
• High integrity, strong judgment, and a track record of working independently on high-impact investigations and policy decisions.

Nice To Haves

• Experience with Snowflake, dbt, and Airflow.
• Experience with Python and Go.
• Familiarity with external fraud tooling (e.g., Sift, Arkose, Stripe Radar) or internal risk platforms.
• Experience with fraud operations at scale, especially in environments offering free-tier services or self-serve onboarding.

Responsibilities

• Lead proactive fraud and abuse hunts at scale by analyzing patterns in customer behavior, platform activity, and financial data.
• Investigate sophisticated abuse scenarios such as account harvesting and reselling, credit card testing, promo exploitation, and unauthorized resource consumption.
• Partner closely with engineering teams in the Security, Billing, Infrastructure, and Product orgs to implement mitigations that preserve platform trust and safety while minimizing impact to legitimate users.
• Use a mix of SQL/data warehouse queries, machine learning, internal tools, and product telemetry to surface anomalies and build repeatable methods to detect new fraud patterns.
• Shape and tune rules, heuristics, internal playbooks, and automated actions for risk scoring, blocking, and escalation workflows.
• Act as a subject matter expert for fraud and cloud capacity management industry trends, collaborating with Finance, Growth, Customer Support, and go-to-market teams on education and cross-functional response.
• Monitor and own metrics such as fraud loss, mitigation efficacy, and false-positive rates, and regularly share insights with stakeholders.
• Contribute to tooling, dashboards, and feedback loops that help the broader team detect fraud faster and act more decisively.

Benefits

• Competitive array of benefits including Employee Assistance Program and flexible time off policy.
• Reimbursement for relevant conferences, training, and education.
• Access to LinkedIn Learning's 10,000+ courses.
• Salary range between $166,400 - $208,000 based on market data, relevant years of experience, and skills.
• Bonus eligibility based on company and individual performance.
• Equity compensation including equity grants upon hire and participation in Employee Stock Purchase Program.
• Commitment to diversity and inclusion.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Industry: Publishing Industries
• Number of Employees: 1,001-5,000 employees