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.
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
Qualification
IdeallyStrong identityExperience with SSO
Required
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.
