Senior Software Engineer, Client Security

- Cross-functional threat response: Collaborate with client, backend, risk, and privacy stakeholders to research malicious tooling, track emerging attacks, and build anti-automation and validation systems.
- AI-driven automation defense: Build client-side defenses against AI-driven automation (LLM-assisted/scripted bots), including behavior modeling, anomaly detection, and proof-of-human signal design.
- On-device ML and content integrity: Secure on-device ML components used in product features-covering model integrity verification, anti-tamper/anti-extraction, encrypted model loading, and secure inference runtimes (e.g., TEE/Secure Enclave)-and research adversarial ML and deepfake vectors impacting client features (e.g., biometrics, media, content) to design on-device detection and mitigation pipelines.

Qualifications

Minimum Qualifications
- Strong passion for information security with hands-on experience in binary security and reverse engineering, including code obfuscation, VMP/virtualization, anti-debugging, anti-injection, and malware analysis.
- Deep understanding of OS internals; proficiency in C/C++, Objective-C, and Java; familiarity with ARM/x86 assembly; solid programming skills and clean coding habits.
- Cross-platform client security experience is preferred; expert-level proficiency in at least one platform (Android, iOS, macOS, or Windows) with the ability to deliver independently.
- Working knowledge of AI security and adversarial ML concepts (e.g., evasion/poisoning attacks, model extraction/inversion, jailbreak/prompt-injection, data exfiltration) and their impact on client-side defenses.
- Experience designing signals and features to differentiate human-device interactions from automated agents and reducing false positives under privacy constraints.

Preferred Qualifications
- Experience with TEE/TrustZone/Secure Enclave, device/app attestation, and secure traffic validation.
- Familiarity with Frida, Xposed, Clang/LLVM, static/dynamic analysis, and symbol/identifier obfuscation and hardening pipelines; experience building large-scale anti-automation and validation systems.
- Experience with on-device ML frameworks (e.g., TensorFlow Lite, PyTorch Mobile, Core ML, Metal, NNAPI) and secure model deployment (e.g., encryption, integrity checks, guarded runtime), as well as client-side bot detection leveraging ML, deepfake/synthetic media detection, content provenance/watermark verification (e.g., C2PA), and privacy-preserving ML (e.g., differential privacy/federated approaches).
- Prior AI red teaming or attack tooling development (e.g., prompt-injection harnesses, adversarial example generation) and collaboration with applied ML teams on guardrails and monitoring.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $212800 - $387600 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.

Client-provided location(s): San Jose, CA

Job ID: TikTok-7627383184665397557

Employment Type: OTHER

Posted: 2026-04-14T20:24:54