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Turing

Deployment Architect

Turing is hiring a Deployment Architect in New York, United States. Level rates it ; you can apply on Turing.

Level's read on this job

  • Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
  • The posting mentions AI research among its tools and skills.
  • Turing has 30 other open roles on Level.
  • Posted in the last few days.

AI in this role

ai-research
About Turing

Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com. 

 

Role: Enterprise AI - Deployment Architect
Location: New York City, Madison Square Park area
Reports to: Head of Engineering, Enterprise AI
Experience Level: 10+ years
Work Model: Hybrid, with regular in-office presence

Why Join Enterprise AI?

Enterprise AI is building the platform that enables secure and reliable deployment of AI systems inside regulated enterprises.

As a Deployment Architect, you will own the deployment architecture for client cloud, dedicated, and sovereign environments. You will help define the security controls, compliance evidence, and deployment patterns required to move enterprise AI systems through vendor reviews and into production.

You will work directly with client security, infrastructure, and compliance teams, including bank and government information security organizations. This is a high-ownership role for someone who combines deep infrastructure security expertise with strong client-facing judgment.

As a Deployment Architect, You Will

Design Enterprise Deployment Architectures

Create secure reference architectures for client cloud environments, dedicated instances, sovereign deployments, and other customer-controlled environments across AWS, Azure, and GCP.

Lead Security and Compliance Readiness

Define security controls, compliance evidence, and deployment standards required for regulated enterprise customers.

Partner with Client Security Teams

Lead vendor-review conversations with bank, government, and other regulated enterprise information security teams. Translate their requirements into clear technical and operational actions.

Build Secure Platform Guardrails

Help implement policy-as-code guardrails, identity controls, key custody models, admission controls, image signing, and other security mechanisms within the platform and its CI systems.

Own Threat Modeling

Evaluate risks associated with agents, connectors, prompt injection, data exfiltration, privileged access, and software supply chains.

Establish Operational Readiness

Help build the incident response, vulnerability management, and security operations processes required to support enterprise deployments.

The Anti-Sell

Hands-on infrastructure security: This is not an application security or GRC-only role. You must have personally designed and operated infrastructure and cloud security systems.

Regulated enterprise complexity: You will work with demanding security, compliance, and vendor-risk teams in regulated environments.

Client-facing accountability: You will be expected to lead security conversations directly with customers and translate technical requirements into practical deployment decisions.

Technical depth: The role requires strong experience across cloud security, Kubernetes security, identity, compliance evidence, infrastructure as code, and enterprise deployment architecture.

Our Enterprise AI Deployment Architects Typically Have

Deep security and cloud architecture experience: Ten or more years in security engineering or cloud architecture, including experience at a regulated company or a vendor that sells into regulated enterprises.

Vendor security review experience: A track record of personally leading a vendor security review through approval at a global bank, government body, or similarly regulated institution.

Compliance program leadership: Experience leading a SOC 2 or ISO 27001 program and producing the technical evidence required for external review.

Multi-cloud infrastructure expertise: Strong knowledge of AWS, Azure, and GCP security architecture, including landing zones, private networking, KMS, and air-gapped deployment patterns.

Kubernetes and identity security expertise: Experience with pod security, admission control, image signing, federation with client identity providers, privileged access, and key custody.

Client-ready threat modeling: The ability to assess risks across agents, connectors, prompt injection, data exfiltration, and software supply chains, and communicate practical mitigations to technical and executive stakeholders.

Candidates whose experience is limited to application security or GRC without hands-on infrastructure experience, or who have never worked directly with clients, will not be a fit for this role.

Top-Tier Candidates Will Have

  • Experience delivering sovereign cloud or data residency solutions.
  • Experience with Saudi, European Union, or other complex regulatory environments.
  • Experience supporting security reviews for financial institutions or government customers.
  • Experience building security controls into infrastructure and CI systems.

Values

  • We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value.

  • We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection

  • We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.

Advantages of joining Turing

  • Work at the frontier of AI, helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks.

  • Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS.

  • Bring frontier AI innovation to the enterprise, applying lessons learned from leading AI labs to solve real-world business challenges.

  • Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies.

  • Move at the pace of AI innovation, with the speed, ownership, and impact of a startup.

 

Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

For applicants from the European Union, please review Turing's GDPR notice here.

 

How we rate this

Deployment Architect at Turing rates 68 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI Research

Questions you could be asked

  1. Tell me about a research question you investigated. What did you find?
  2. Describe a typical day in a role like this one: which parts run through AI directly?
  3. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: AI Research. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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