{"id":3363903,"url":"https://alion.io/job/servicenow-staff-software-engineer-platform-security","title":"Staff Software Engineer - Platform Security","company":{"id":97,"name":"ServiceNow","domain":"servicenow.com","url":"https://alion.io/company/servicenow","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":80,"open_postings":37,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":18,"computed_at":"2026-10-29T05:49:05Z"}},"role":"Backend","role_family":"Backend","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Diego, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":149800,"max":262200,"currency":"USD","period":"year","gross":null,"usd_annual":262200},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"CI/CD","optional":false},{"name":"DNS","optional":false},{"name":"Helm","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"PKI","optional":false},{"name":"ServiceNow","optional":false},{"name":"TCP/IP","optional":false},{"name":"Threat Modeling","optional":false},{"name":"FedRAMP","optional":true},{"name":"IAM","optional":true},{"name":"LLM","optional":true}],"status":"live","first_seen_at":"2026-10-27T20:04:53Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-29T09:16:05Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone-freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow- helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.\nJoin us to put AI to work for people.\nPlatform Security Team\nPlatform Security builds foundational security infrastructure and AI-driven detection systems for enterprise-scale operations. Our mission is to make security proactive, intelligent, and seamlessly integrated into the ServiceNow platform. Outbound Security within Platform Security owns the controls on traffic leaving the ServiceNow platform across multiple domains: egress filtering and policy, outbound proxying, SSRF protection, data exfiltration prevention, and workload egress identity for a SaaS platform. This is core, regulated-environment security engineering.\nRole Summary\nAs a Staff AI Security & Outbound Security Engineer, you will architect and deliver enterprise-scale security solutions that integrate outbound security systems with machine learning, reasoning engines, and real-time inference. You will bring deep expertise in network and application egress security, strong technical leadership, and hands-on machine learning depth. You will design and operate intelligent, adaptive security systems for egress control, outbound proxy infrastructure, and exfiltration detection at SaaS scale.\nWhat You Get to Do in This Role\nDesign, build, and maintain high-quality, scalable, secure outbound security services meeting FIPS compliance and regulated-environment requirements\nArchitect and operate mission-critical egress services with reliability and security as first-class design constraints, not afterthoughts\nOwn services end-to-end on Kubernetes in a multi-tenant SaaS environment: deployment, scaling, on-call, incident response\nBring a security mindset to every design review: threat model the feature, not just the happy path. This is a deliberate area we're leveling up as a team\nEvaluate where AI/ML has a legitimate role in outbound security, such as anomaly detection in egress traffic, ML-assisted destination risk scoring, and AI-assisted code review for SSRF and unsafe outbound-request patterns, and separate that from where it's a distraction\nCollaborate with product owners, security architects, and platform teams to translate compliance and security requirements into working outbound security frameworks\nMentor engineers on secure coding, outbound-request pitfalls (SSRF, DNS rebinding, open redirects, unrestricted egress), and design review rigor\nStay current on evolving exfiltration techniques and egress-security advancements, including post-quantum readiness for outbound TLS, and bring that forward before it's a compliance deadline\nBasic Qualifications\n8+ years of professional software engineering experience; Java, Go, or a comparable strongly-typed language at production scale\nStrong CS fundamentals: data structures, algorithms, OO design, distributed systems tradeoffs\nProduction experience running services on Kubernetes (deployments, Helm, CI/CD) in a SaaS/multi-tenant environment. This is assumed, not a differentiator\nWorking understanding of core network and application security concepts (TCP/IP, DNS, HTTP, TLS/PKI fundamentals, proxies, firewalls, allowlisting/denylisting)\nDemonstrated security-first engineering habits: secure coding practices, threat modeling, code review discipline\nPreferred Qualifications\nDirect experience in outbound/egress security, forward proxies, SSRF mitigation, DNS security, or data loss/exfiltration prevention, including egress gateways, network policy enforcement, or TLS inspection\nAuthN/AuthZ, IAM, Certificates, Identity, secure connectivity and external network topology experience\nSome hands-on AI/ML exposure. Not a research background, but real experience applying ML techniques to security/ops problems (anomaly detection, risk scoring, log/telemetry analysis) or critically integrating LLM tooling into engineering workflows\nExperience with regulated environments (FIPS 140-2/3, FedRAMP, Common Criteria, or similar)\nExposure to post-quantum cryptography in the context of outbound TLS and secure communications\nTrack record mentoring engineers and raising the security bar on a team, not just shipping features\nFor positions in this location, we offer a base pay of $149,800 - $262,200, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.\n Work Personas\nWe approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.\nEqual Opportunity Employer\nServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.\nAccommodations\nWe strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact  for assistance.\nExport Control Regulations\nFor positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.\nFrom Fortune. ©2026 Fortune Media IP Limited. All rights reserved. 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