Most Loved Workplace® Certified JobStaff Security Software Engineer, AI Security Engineering
Most Loved Workplace® Certified JobAbout the Role
At Databricks, a Most Loved Workplace® certified employer in the Technology space, Democratizing data and AI for every organization worldwide.
<p data-pm-slice="1 1 []"><em>RDQ226R605; This role can be based remotely anywhere in the United States.&nbsp;</em></p>
<p>&nbsp;</p>
<p>The AI Security Engineering team at Databricks builds the security tools, detection systems, and engineering infrastructure that protect Databricks' AI platform and the AI capabilities our customers depend on. We are the builders — designing and shipping security tooling that scales AI threat detection, automates security assessment of AI systems, and gives Databricks and its customers high-confidence assurance that AI capabilities are operating securely. We sit at the intersection of security engineering and AI systems: we understand how AI systems work, how they can be attacked, and how to build engineering solutions that keep them safe at scale.</p>
<p>---</p>
<p>As a <strong>Staff Security Software Engineer</strong> on the AI Security Engineering team, you set the technical direction for AI security engineering at Databricks — defining the architecture, standards, and methodology by which the team builds tooling for AI security assessment, detection, and defense. You are recognized across the Security organization as the authority on AI security engineering: the person engineering leadership consults when AI security tooling decisions have organizational-scale consequences.</p>
<p>You operate across team and organizational boundaries — aligning the AI Security Engineering team's technical roadmap with the detection, GRC, and product security teams that depend on its outputs, and driving AI security engineering standards that the whole security organization can adopt.</p>
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<h5>The Impact You Will Have</h5>
<h6>AI Security Engineering Architecture</h6>
<ul>
<li>Define the architecture and technical strategy for Databricks' AI security tooling platform — spanning adversarial testing, behavioral monitoring, threat detection, and automated assessment of AI components</li>
<li>Set engineering standards for the team: design review processes, reliability requirements, observability practices, security properties of the tooling itself, and integration patterns with downstream consumers</li>
<li>Own the technical decisions on how the team's systems scale to cover Databricks' growing AI surface, how they integrate with product security and detection pipelines, and what tooling capabilities to build vs. buy vs. open-source</li>
</ul>
<h6>AI Threat Detection at Scale</h6>
<ul>
<li>Lead the design and development of AI platform capabilities that operate at production scale — behavioral analysis of usage, detection of prompt injection attempts, anomaly detection on agentic workflow behavior</li>
<li>Define the methodology for AI security assessment: how Databricks systematically evaluates new AI capabilities against a comprehensive threat model before deployment and monitors them continuously after</li>
<li>Drive technical strategy for AI red-teaming tooling: automated adversarial testing platforms that simulate how real attackers attempt to abuse Databricks' AI systems</li>
</ul>
<h6>Cross-Organizational Technical Leadership</h6>
<ul>
<li>Serve as the technical authority on AI security engineering for the Product Security, SITH, IR, and ConMon teams — ensuring that AI security tooling outputs integrate cleanly into their workflows and meet their detection and assessment needs</li>
<li>Represent AI Security Engineering in architecture reviews, platform security decisions, and cross-team technical discussions where AI security engineering considerations are material</li>
<li>Establish AI security engineering standards that teams building AI-connected systems can adopt — reusable patterns for securing AI components in the Databricks platform</li>
</ul>
<h6>Mentorship &amp; Team Capability</h6>
<ul>
<li>Mentor senior and mid-level engineers on AI security engineering architecture, adversarial threat modeling, and technical leadership</li>
<li>Lead design reviews, define team engineering practices, and drive continuous improvement in the quality and reliability of AI security tooling</li>
</ul>
<p>---</p>
<h5>What We Look For</h5>
<ul>
<li>7–10 years of experience in security software engineering, security engineering, or a closely related discipline; with demonstrated technical leadership of security tooling programs and organizational-level impact</li>
<li>Expert Python engineering: designs and delivers production systems at scale; understands observability, reliability engineering, and how security tooling integrates into larger security operations ecosystems</li>
<li>Deep expertise in AI/ML security — adversarial ML, prompt injection, model security, agentic framework trust boundaries — at both a research-informed and engineering-practical level</li>
<li>Experience designing security tooling architectures that span multiple teams and systems — not just building features, but defining how the platform is structured, scaled, and maintained</li>
<li>Strong technical communicator: can align engineering and security leadership on architectural direction and drive cross-team adoption of standards and patterns</li>
<li>Track record of shipping high-quality security tooling that other teams depend on in production</li>
</ul>
<h5>Nice to Have</h5>
<ul>
<li>Research contributions or deep familiarity with adversarial ML, AI safety, or AI red-teaming methodology</li>
<li>Experience with MLOps platforms, AI serving infrastructure, or AI platform security at cloud scale</li>
<li>Familiarity with AI governance standards (NIST AI RMF, ISO/IEC 42001, EU AI Act technical provisions) as they apply to security engineering</li>
<li>Open-source contributions or publications in AI security, adversarial ML, or security tooling</li>
</ul><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p>&nbsp;</p>
<p><strong>Pay Range Transparency</strong></p>
<p><span style="font-weight: 400; font-size: 14px;">Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.&nbsp; Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page <a href="https://www.Databricks.com/sites/default/files/2024-08/us-pay-zone-mapping.pdf">here</a>.<br></span></p>
<p>&nbsp;</p></div><div class="title">Zone 1 Pay Range</div><div class="pay-range"><span>$289,200</span><span class="divider">&mdash;</span><span>$397,650 USD</span></div></div><div class="pay-input"><div class="title">Zone 2 Pay Range</div><div class="pay-range"><span>$260,300</span><span class="divider">&mdash;</span><span>$357,950 USD</span></div></div><div class="pay-input"><div class="title">Zone 3 Pay Range</div><div class="pay-range"><span>$245,800</span><span class="divider">&mdash;</span><span>$338,050 USD</span></div></div><div class="pay-input"><div class="title">Zone 4 Pay Range</div><div class="pay-range"><span>$231,400</span><span class="divider">&mdash;</span><span>$318,100 USD</span></div></div></div><div class="content-conclusion"><p><strong>About Databricks</strong></p>
<p><span style="font-family: arial, sans-serif;">Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on&nbsp;<span style="color: rgb(255, 54, 33);"><a style="color: rgb(255, 54, 33);" href="https://twitter.com/Databricks" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://twitter.com/Databricks&amp;source=gmail&amp;ust=1700237575733000&amp;usg=AOvVaw03FL8fJvOD97ytN02f5G2C">Twitter</a>,&nbsp;<a style="color: rgb(255, 54, 33);" href="https://www.linkedin.com/company/Databricks" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://www.linkedin.com/company/Databricks&amp;source=gmail&amp;ust=1700237575733000&amp;usg=AOvVaw15dLk3q8VxTfHEgCUg7NSt">LinkedIn</a>&nbsp;<span style="color: rgb(0, 0, 0);">and</span>&nbsp;<a style="color: rgb(255, 54, 33);" href="https://www.facebook.com/databricksinc" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://www.facebook.com/databricksinc&amp;source=gmail&amp;ust=1700237575733000&amp;usg=AOvVaw39EcncitnlqV72EG2-RqXJ">Facebook</a></span>.<br><br><strong>Benefits<br><br></strong></span>At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click <a href="https://docs.google.com/document/d/154un3e8Xav4BceOSlcYFZRGEuQI54xMxVydRwQn54eQ/edit?usp=sharing">here</a>.<br><br></p>
<p><strong>Our Commitment to Diversity and Inclusion</strong></p>
<p>At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.</p>
<p><strong>Compliance</strong></p>
<p><strong><span style="font-weight: 400;">If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.</span></strong></p></div>
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Why This Is a Most Loved Workplace® Certified Job
Systemic Collaboration
As Databricks continues our rapid growth, we strive to maintain a culture as open and transparent as it was in Databricks’s early days. Making sure employees have regular access to our CEO and co-founders to hear directly about our vision and priorities helps our employees forge a connection between Databricks priorities and their daily work.
Positive Vision for the Future
Databricks’ culture principles are derived from an internal study of the behaviors that have led to high impact work at Databricks. These values have a direct impact on company culture and play a large part in connecting teams across the organization. We believe in being customer-obsessed, truth-seeking, operating from first principles, having a bias for action, and putting Databricks first. Our co-founders are fully involved in day-to-day operations, including business and technical reviews, working alongside our team members to ensure that we are always aligned with our values.
Alignment of Values
Databricks’ CEO and Co-founder, Ali Ghodsi leads by example with a focus on truth-seeking and first principles thinking, two of Databricks’ core values that stay true to Databricks’s origins in academia. He champions the importance of data and reason to question biases and inform decisions. Ali remains hands-on with research and development and hosts company-wide weekly all hands, with a CEO “ask me anytime” session at the beginning of every agenda. His transparency and accessibility are core to the open and collaborative culture of Databricks.
Respect
At Databricks, we cultivate an environment where all employees can bring their unique selves and are empowered to do the best work of their careers. To ensure all voices are heard and ideas are valued, we conduct annual culture and pulse surveys and host all-hands Q&As to collect feedback from all employees. We then report back to Databricks on the specific changes implemented from the feedback collected to ensure employees feel heard and that their feedback is valued. In addition, we invest in our seven Employee Resource Groups (ERGs) that offer support and employee engagement events for individuals from underrepresented backgrounds and allies.
Killer Outcomes
Databricks prioritizes offering an exceptional employee experience by investing in tools, workspaces, and community-building. Our collaboration-first, hybrid model offers flexibility with in-person touchpoints like our annual employee kickoff, weekly CEO all-hands with happy hours, and monthly team building budgets. We are especially focused on maintaining a culture of transparency, honesty, and trust, with leaders actively engaging across channels like Slack and all hands while also championing inclusion efforts through ERG sponsorship. These initiatives help our team feel connected, valued, and empowered to do their best work.
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