> Markdown version of [/jobs/ext/4637146-management-platform-infrastructure-audit](https://www.wearedevelopers.com/jobs/ext/4637146-management-platform-infrastructure-audit). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Management, Platform & Infrastructure Audit - **Company:** Internal Audit Foundation - **Location:** San Jose, United States - **Experience:** Expert - **Salary:** $171,000 - $257,000 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Computing, Cloud Computing Security, Code Review, Information Engineering, Extract Transform Load (ETL), DevOps, Identity and Access Management, Key Management, Network Segmentation, Open Source Technology, Systems Development Life Cycle, Reliability Engineering, Blockchain, Azure Machine Learning, Software Engineering, Feature Store, IT General Controls (ITGC), Containerization, Kubernetes, Data Lineage, Machine Learning Operations, Terraform, Data Pipelines, Human in the Loop, Docker - **Published:** November 8, 2026 - **Apply:** https://startup.jobs/senior-management-platform-infrastructure-audit-okx-10716923 ## About the Role * Crypto & Blockchain Acumen: Prior experience at a crypto exchange or with a crypto product is preferred. * Critical Thinking for Complex Environments: A proven capacity to analyze novel technical and control environments unique to crypto, identify intricate root causes, and propose effective, context-specific remediation that engineering teams will actually adopt. * Breadth Across Adjacent Platform Domains: Demonstrable experience auditing control design and operating effectiveness in several of the following: + Cloud security and identity - IAM, network segmentation, secrets management, encryption and key management + Site reliability and resilience - observability, incident and problem management, capacity, backup and disaster recovery + Software development lifecycle - code review, branch protection, artifact integrity, secure SDLC, third-party and open-source dependency risk + Data engineering and analytics - integrity and quality of data pipelines and ETL processes + AI/ML platform and MLOps - model registries, feature stores, inference infrastructure, and the data feeding them, * Cloud or Security Certifications: AWS or GCP professional-level certification, Certified Kubernetes Administrator (CKA), CISA, CISSP, or CCSK/CCSP. * Crypto and blockchain literacy: regulated financial-services, fintech, or crypto experience. * Mandarin speaking ## Description As Senior Manager, Platform & Infrastructure Audit, you'll be a hands-on, deeply technical individual-contributor auditor who owns critical assurance projects spanning the cloud infrastructure and DevOps lifecycle, from platform build and configuration through CI/CD pipelines and hands-on ITGC validation. You'll bring subject matter expertise to both dimensions of AI in scope: auditing AI (assessing how OKX's AI/ML systems are built, governed, and monitored) and auditing with AI (applying AI tools to your own scoping, testing, and reporting) while also flexing into adjacent domains such as cloud security and identity, resilience engineering, secure SDLC, and data engineering. You'll help shape the risk-based audit plan by identifying emerging infrastructure risks, and partner closely with Engineering, SRE, and Security stakeholders to deliver findings and recommendations that hold up in a fast-moving, high-technology crypto environment., * Cloud Infrastructure & Platform Engineering Audit (SME): Deep, hands-on expertise auditing cloud platforms (Alibaba Cloud, AWS), containerization and orchestration (Docker, Kubernetes), CI/CD pipelines, and infrastructure-as-code (Terraform, Helm). * AI Use, Adoption & Governance: Two dimensions, both required. + Auditing AI: Assessing how AI/ML systems are built, deployed, and monitored - model and data lineage, training-data provenance and quality, access to models and prompts, human-in-the-loop and approval controls, evaluation and drift monitoring, and alignment to emerging AI governance and regulatory expectations. + Auditing with AI: A demonstrated bias toward using AI in your own audit work - scoping, evidence review, control testing, script generation, and reporting - and an interest in helping the function build reusable AI-enabled audit tooling.