Deployment Architect
New York, New York, United States
Posted 15h ago
Job Location
New York, New York, United States
Tech Stack
Remote Work Policy
On-site
Categories
AI Infrastructure Engineer
About the job
Turing's mission is to accelerate superintelligence to drive real economic progress. We work with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks. We also partner with Fortune 500 enterprises across various sectors to build and deploy end-to-end agentic AI systems within mission-critical workflows. By operating on both sides, we bridge the gap between frontier research and enterprise deployment, translating real-world deployment signals into better data, evaluations, and more capable models.
Responsibilities
- Design secure reference architectures for client cloud environments, dedicated instances, and sovereign deployments across AWS, Azure, and GCP.
- Define security controls, compliance evidence, and deployment standards for regulated enterprise customers.
- Lead vendor-review conversations with bank, government, and other regulated enterprise information security teams, translating their requirements into technical actions.
- Implement policy-as-code guardrails, identity controls, key custody models, admission controls, and image signing within the platform and CI systems.
- Conduct threat modeling for risks associated with agents, connectors, prompt injection, data exfiltration, privileged access, and software supply chains.
- Help build incident response, vulnerability management, and security operations processes for enterprise deployments.
Requirements
- Ten or more years in security engineering or cloud architecture, including experience at a regulated company or a vendor selling into regulated enterprises.
- Proven track record of leading a vendor security review through approval at a global bank, government body, or similarly regulated institution.
- Experience leading a SOC 2 or ISO 27001 program and producing technical evidence for external review.
- Strong knowledge of AWS, Azure, and GCP security architecture, including landing zones, private networking, KMS, and air-gapped deployment patterns.
- Expertise in Kubernetes and identity security, including pod security, admission control, image signing, federation with client identity providers, privileged access, and key custody.
- Ability to assess risks across agents, connectors, prompt injection, data exfiltration, and software supply chains, and communicate practical mitigations to stakeholders.