Sr. Staff Platform Security Engineer, Cloud Infrastructure

Lead security engineering for cloud infrastructure that powers Groq’s inference platform.

Responsibilities

• Set technical direction and own architecture for critical platform security capabilities across identity, authorization, infrastructure security, encryption, key management, and auditability.
• Design and build identity and access systems covering authentication, federation, authorization, workload identity, lifecycle provisioning, and administrative access.
• Build and scale security capabilities for Kubernetes and other distributed infrastructure using software, policy, automation, APIs, controllers, Infrastructure-as-Code, and GitOps.
• Architect security controls and isolation mechanisms for multi-tenant systems across compute, network, storage, and control-plane boundaries.
• Own infrastructure lifecycle security, including secure provisioning, secrets and credential management, encryption, and certificate lifecycle.
• Develop production software and automation so secure infrastructure patterns are reliable, scalable, and adoptable by engineering teams.
• Lead security-sensitive platform designs and changes by translating complex risks and requirements into practical engineering decisions and scalable platform capabilities.
• Shape security architecture and technical standards across Platform Engineering and influence designs beyond owned systems.
• Partner across engineering and security to build capabilities that strengthen customer trust, platform reliability, and support compliance requirements.
• Communicate security architecture, technical tradeoffs, and risk clearly to engineers, technical leadership, and security leadership.

Requirements

• 6+ years of software engineering experience building complex infrastructure or distributed systems, with deep cloud and platform security experience in identity and access, Kubernetes, or related infrastructure security domains.
• Proven experience setting technical direction and owning complex security architecture across multiple systems, teams, or infrastructure domains.
• Deep knowledge of identity and access technologies: OIDC, SAML, SCIM, RBAC, workload identity, short-lived credentials, and multi-factor authentication.
• Deep experience designing security for multi-tenant systems and isolation across network, compute, storage, and control-plane boundaries.
• Hands-on Kubernetes security expertise, including RBAC, admission control, service-account and workload identity, secrets and encryption, policy enforcement, and node security.
• Strong understanding of secrets management, encryption, key management, certificate lifecycle, and secure credential management.
• Strong software engineering skills in Go, Python, or similar languages, with experience designing, building, and operating production systems.
• Software-first approach to security with experience building controls through APIs, controllers, automation, policy, Infrastructure-as-Code, GitOps, or similar approaches.
• Experience leading ambiguous, cross-functional technical initiatives and influencing engineering direction across teams.
• Ability to reason about complex security systems end to end and communicate technical risk and architectural tradeoffs to different audiences.
• Experience building identity, key-management, network security, or infrastructure security capabilities for cloud platforms is valuable.
• Experience with network policy and encryption or security for high-performance storage and distributed infrastructure is valuable.
• Experience translating security and compliance requirements into automated evidence and production-ready controls is valuable.
• Experience building Kubernetes operators, admission webhooks, or similar infrastructure automation is valuable.

Technologies

• Kubernetes
• Go
• Python
• OIDC
• SAML
• SCIM
• RBAC
• Infrastructure-as-Code
• GitOps
• APIs
• Controllers
• Multi-factor authentication
• Short-lived credentials

Location & Work Model

• San Francisco Bay Area, CA (hybrid)
• Based in one of the three hiring hubs: Dallas, San Francisco, or New York City area
• Remote flexibility available while local Groq office is established; role expected to transition onsite once the office opens

Compensation

• Total cash salary range: USD 341,400 - 401,600 per year
• Inclusive of potential bonus value
• Placement depends on geographic location, experience, skills, and alignment with internal compensation standards
• International compensation varies by local market dynamics
• Long-Term Incentive (LTI) Program and a robust suite of employee benefits

Mission

• Build and scale security foundations that enable customers to run sensitive AI workloads with confidence on Groq’s inference platform

Benefits

• Long-Term Incentive (LTI) Program
• Robust suite of employee benefits

U.S. Export Control Notice

• Access to technology and/or information may be subject to U.S. export control laws, including the Export Administration Regulations (EAR)
• Candidates must qualify as U.S. Persons for export control purposes (U.S. citizen, U.S. lawful permanent resident, or a protected individual under 8 U.S.C. § 1324b(a)(3)), or be eligible for an applicable export license

Non-U.S. Export Control Notice

• Access to technology and/or information may be subject to U.S. export control laws (EAR) and applicable local laws and regulations
• Candidates must meet all relevant export control eligibility criteria

Equal Opportunity Employer

• Committed to an inclusive environment and nondiscrimination across protected characteristics
• All qualified applicants receive consideration without regard to race, color, religion, national origin, sex, age, disability, genetic information, protected veteran status, or other protected characteristics under applicable law
• Does not tolerate discrimination or harassment based on protected characteristics

Reasonable Accommodations

• Groq provides reasonable accommodations for qualified individuals with physical or mental disabilities
• For accommodation requests related to application or hiring process: [email protected] (considered on a case-by-case basis)

Offers Contingent on Verification

• Offers of employment are contingent upon verification of applicant identity and employment authorization per federal law

Artificial Intelligence in Hiring Process

• AI tools or automated systems may be used to assist with reviewing applications, evaluating qualifications, scheduling interviews, analyzing assessment responses, or supporting recruiting operations
• Tools assist but do not replace human decision-making; hiring decisions are subject to human review
• Groq may process application materials, interview responses, assessments, and where applicable audio/video/transcript data
• Consent will be requested if legally required for technologies that analyze biometric or video interview data
• Candidates may request reasonable accommodations, an alternative evaluation process, additional information about AI use in hiring, or review of certain automated decisions by contacting [email protected]