HiddenLayer

HiddenLayer

HiddenLayer offers a noninvasive AI security solution to protect enterprises' machine learning models, ensuring the safeguarding of critical products without adding complexity or requiring access to raw data.

IT Services
11-50
Founded 2022
$88M raised

Description

  • Lead discovery workshops to understand customer missions, AI initiatives, architectures, data pipelines, and security and compliance requirements.
  • Translate ambiguous mission needs into scoped proof-of-value engagements with measurable success criteria, timelines, and exit conditions.
  • Qualify technical fit and clearly communicate what the platform will and will not do.
  • Architect and deploy the platform in SaaS and fully airgapped environments, including packaging artifacts for restricted networks.
  • Stand up and administer Kubernetes-based deployments using Docker, Helm, and private registries across cloud and on-premises environments.
  • Build mission-focused demonstrations and proof-of-concept AI applications and integrate SDKs and APIs to protect them.
  • Advise customers on securing models, AI applications, data pipelines, and supporting infrastructure using relevant AI security frameworks.
  • Deliver live demonstrations, architecture sessions, evaluation reports, reference architectures, and integration guides for diverse audiences.
  • Support onboarding, troubleshooting, and integration during evaluations and initial deployments in partnership with Customer Success.
  • Represent HiddenLayer at conferences, government engagements, webinars, and technical events, and feed learnings back to Product, Research, and Engineering.

Requirements

  • 5+ years of experience in solutions architecture, solutions engineering, applied AI engineering, or a similar customer-facing technical role.
  • Direct support of federal customers across the IC, DoD/DoW, DHS, or civilian agencies.
  • Strong Python skills and hands-on experience across the modern AI stack, including model formats, inference, LLM APIs, retrieval and agentic patterns, PyTorch, Hugging Face, and ONNX.
  • Hands-on experience with Docker, Kubernetes, and Helm, including moving artifacts into restricted or fully disconnected environments.
  • Understanding of MLOps and CI/CD for moving models from data to production, including where security belongs in the pipeline.
  • Working security literacy, including adversarial machine learning concepts and common AI attack classes.
  • Experience operating inside federal missions and speaking to mission outcomes with specificity.
  • Comfort presenting live demos, whiteboard sessions, conference talks, and executive briefings.
  • Willingness and ability to travel as needed for customer engagements and industry events.
  • Preferred experience securing AI/ML systems in production or supporting AI programs in classified environments.
  • Preferred experience with ONNX, SafeTensors, GGUF, and pickle-based serialization.
  • Preferred experience red-teaming LLM applications or using AI security and evaluation tooling.
  • Preferred certifications such as Kubernetes, AWS, Azure, CISSP, or Security+.
  • Preferred public work such as GitHub repositories, Hugging Face artifacts, conference talks, or technical writing.

Benefits

  • Fully remote global work environment with a home office setup stipend, annual equipment upgrades, and a monthly internet/phone stipend.
  • Unlimited and flexible time off for salaried employees plus 15 paid company holidays.
  • Dedicated learning and development fund for training, conferences, certifications, and industry events.
  • Opportunity to work for a venture-backed company that recently closed a $50M funding round.
  • Commitment to diversity, equity, and inclusion as an equal opportunity employer.

Interested in this position?

Apply directly on the company website

Apply Now

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