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Lead Senior Security Engineer (Enterprise AI Platform)

Evolver
AI GovernanceOn-siteFull-timePalo Alto, CA

Evolver is hiring for the job of Lead Senior Security Engineer (Enterprise AI Platform), Palo Alto, CA (On-site). This is an AI Governance job in the governance, risk, and compliance field. Review the full details below and apply directly with Evolver.

Organization: EvolverLocation: Palo Alto, CAWorkplace: On-siteFocus: AI GovernancePosted: Oct 25, 2026
Evolver is hiring for this AI Governance job in Palo Alto, one of the metros GRC Careers tracks for governance, risk, and compliance hiring. See other GRC jobs in Palo Alto →

About Us

Evolver is building an AI platform that takes on core enterprise functions under the CFO agenda, including finance, tax, audit, risk, compliance, and operational efficiency. Our platform is deployed with Fortune 1000 companies and professional services firms to automate complex, regulated workflows that require high accuracy, strong governance, explainability, and enterprise-grade security.

We are looking for a Lead Senior Security Engineer to own and scale the security architecture, engineering practices, and customer deployment posture of our platform as we expand across large enterprise environments. This role will strong report directly to the CTO and Co-Founder and serve as the senior security leader responsible for ensuring that security is built into the platform, product architecture, and customer deployment model.

Role Overview

As Lead Senior Security Engineer, you will lead the security design, architecture, and implementation for Evolver’s AI platform. You will be responsible for ensuring that the platform, its cloud infrastructure, AI workflows, data pipelines, enterprise integrations, and customer deployments meet the security, privacy, and control expectations of Fortune 1000 organizations.

This is a hands-on leadership role. You will set security direction, define architecture, guide implementation, support enterprise deployments, and personally implement critical security capabilities. You will work closely with Cloud Engineers, DevOps Engineers, GenAI Engineers, and Forward Deployed Engineers to embed security into every layer of the platform and deployment lifecycle.

The ideal candidate combines deep technical security expertise with the ability to operate directly with engineers and enterprise customers.

Key Responsibilities

Lead platform security architecture and implementation
Own the security architecture for Evolver’s AI platform across application security, cloud infrastructure, data protection, identity and access management, tenant isolation, auditability, and secure enterprise integrations.
Design secure deployment patterns for Fortune 1000 customers
Define and implement secure customer deployment models hosted on cloud and/or within customer-controlled environments. Design deployment patterns that support SSO, RBAC, API integrations, customer-controlled environments, secure data ingestion from enterprise systems, tenant isolation, customer-specific encryption at rest and in transit, secure key management, private networking, and enterprise-grade monitoring and auditability.
Embed security into engineering and operations
Partner with Cloud Engineers, DevOps Engineers, GenAI Engineers, and Forward Deployed Engineers to integrate security into CI/CD, infrastructure-as-code, container deployments, secrets management, vulnerability management, monitoring, incident response, and production operations.
Secure AI platform capabilities
Lead security GenAI workflows, including prompt and data isolation, retrieval security, model access controls, secure tool use, adversarial testing, output governance, audit trails, and controls around third-party model consumption.
Serve as the senior security counterpart for enterprise customers and compliance
Lead technical security discussions with Fortune 1000 customers, support procurement and vendor risk reviews, translate customer requirements into platform capabilities, and partner with compliance teams on SOC 2, ISO 27001, SSPA, customer audits, control evidence, and security documentation.

Qualifications

strong 8+ years of experience in security architecture and engineering
Experience should include application security, cloud security, platform security, enterprise SaaS security, or security architecture for complex, data-intensive systems.
Ideally, some experience securing AI platform capabilities.
Proven ability to design and implement enterprise-grade security architecture
Strong track record securing SaaS platforms, cloud-native systems, customer-facing products, or platforms deployed into large enterprise environments.
Deep hands-on cloud and infrastructure security expertise
Strong experience with cloud security architecture, preferably Azure, including IAM, networking, private endpoints, containers, key management, encryption, logging, monitoring, workload identity, and infrastructure security.
Strong identity, access control, and application security background
Experience with SSO, SAML, OIDC, RBAC, service identities, least-privilege access models, secure SDLC, threat modeling, API security, secrets management, vulnerability management, and secure coding practices.
Experience working directly with enterprise customers and cross-functional engineering teams
Ability to lead customer security reviews, procurement assessments, vendor risk discussions, and deployment security planning while partnering effectively with Cloud, DevOps, GenAI, platform, and Forward Deployed Engineering teams.

strong

Benefits

Competitive Compensation: Tailored to your experience and skill set.
Flexible Work Arrangements: Hybrid working model for work-life balance.
Career Growth: Opportunities for professional development and leadership roles.
Innovative Culture: Work on transformative technologies and make an impact in the AI space.
Comprehensive Benefits: We cover top-tier medical, dental, and vision insurance plans for employees, ensuring access to high-quality healthcare and peace of mind. Free lunch in office everyday.

Location and market context

This job is based in Palo Alto on-site. Local candidates benefit from being close to Evolver's teams and regional hiring market. Confirm the exact in-office expectation and any relocation support with the employer.

About AI governance jobs

AI governance sits at the intersection of policy, risk, and engineering. Teams are standing up model inventories, use-case intake and review, risk classification, and control monitoring as regulation and board scrutiny of AI intensify. Jobs like this one are typically evaluated against frameworks such as NIST AI RMF, ISO/IEC 42001, the EU AI Act, and internal model-risk and privacy practices.

How to position yourself for this AI governance job

Strong candidates emphasize experience translating policy into operational controls, working across legal, compliance, security, product, and data teams, documenting AI system risks, and supporting governance processes. In your resume and outreach, tie your experience to how Evolver would apply NIST AI RMF, ISO/IEC 42001, the EU AI Act, and internal model-risk and privacy practices, and lead with concrete outcomes rather than duties.

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