Security Research Engineer

General

• Seniority: Mid-level (IC2). 3+ years of hands-on experience in security research, offensive security, or fraud analysis.

• Team: Engineering.

• Employment Type: Employee or Contractor.

• Schedule: Full-time.

• Work Arrangement: Full remote possible, with availability for periodic meetings and collaboration sessions.

Responsibilities

As a Security Research Engineer, your core responsibilities will include:

Threat & Fraud Research

• Proactively studying new threats and technologies to stay up to date with modern fraud scenarios.

• Investigating advanced fraudster tactics, including account takeover, social engineering, bot-driven fraud, botnets, and proxy networks.

• Reverse engineering fraud tools, analyzing the scripts and malware used in large-scale fraud, and understanding their functionality and weaknesses.

• Studying OS and browser security internals, including browser tracking protections, and identifying how fraudsters bypass defenses.

Detection Building & Research Execution

• Running fraud analysis investigations to identify attacker techniques and weaknesses.

• Testing our fraud detection systems to find gaps and evasion techniques, with a focus on fingerprinting evasion and browser and mobile fraud automation.

• Developing proof-of-concept solutions that demonstrate improvements to our fraud prevention systems.

• Owning the problem end to end, from research finding through design and implementation to a released detection or feature in the product, with the support of the rest of the engineering team.

• Building custom research tools that speed up research and intelligence gathering.

Improving the Product

• Proposing new detection methods that improve the detection efficacy of the whole product.

• Detecting and analyzing new fraudster tactics and documenting them for further research.

• Supporting fraud investigations so that other teams can respond faster.

• Presenting detection improvements and research findings to the team.

Collaboration & Influence

• Working with the rest of the engineering team and with data scientists to turn research findings into improved detection models.

• Communicating findings clearly so that stakeholders understand evolving fraud techniques.

• Driving improvements in fraud detection techniques to stay ahead of new threats.

Qualifications

Must Have:

• Proven hands-on experience in security research, offensive security, or fraud analysis, ideally in fintech, banking, or cybersecurity.

• Solid understanding of web and mobile security, including browser tracking protections, OS security features, and browser internals.

• Expertise in device and browser fingerprinting and in the evasion techniques fraudsters use to bypass detection.

• Strong knowledge of fraudster tactics and tooling, including account takeover, social engineering, bot-driven fraud, botnets, and proxy networks.

• Hands-on experience with security tools such as Burp Suite, Wireshark, IDA Pro, and Frida.

• Ability to reverse engineer scripts, tools, and malware used in fraud.

• Solid software engineering skills, including writing production-quality, tested code, working with version control and code review, and building your own research tools and prototypes.

• Ability to own a problem from idea to release, pulling in help from the team where needed rather than waiting for direction.

• Ability to document findings clearly and explain complex attacker techniques to engineers, data scientists, and non-technical stakeholders.

Nice to Have:

• Experience shipping detection logic in a fraud, anti-bot, or security product.

• Experience verifying detection techniques on large datasets (for example with Pandas or PySpark).

• Experience building automation for fraud research and intelligence gathering.

• Research experience with OS-level exploits and anti-tracking features on mobile and desktop platforms.

• Experience mentoring other researchers or leading research initiatives across teams.

• Published security research, CTF experience, or conference talks.

• Familiarity with modern technology stacks and the unique challenges of a startup environment.

What We Value

• Extreme Ownership: Taking initiative, driving results, and passionately owning project outcomes

• Deep Understanding: Preference of deeply understanding topics and systems from first-principles over opinions, guesses and superficial knowledge

• Integrity: Consistently adhering to strong moral and ethical principles, acting with honesty, accountability and transparency

• Collaboration: Building positive, efficient relationships, expressing in precise and efficient way

• Innovation and Adaptability: Continuously seeking improvement, being open to new ideas, and making data-driven decisions