WHAT YOU'LL DO:
- Lead secure deployment of LLMs (including on-prem), ensuring encryption and strict access controls.
- Enforce data protection for sensitive info (PHI, PII, financial data) and ensure compliance with HIPAA and other standards.
- Embed Responsible AI practices, including safeguards against misuse, jailbreaking, and adversarial threats.
- Identify and mitigate AI/ML risks throughout the model lifecycle—from development to operations.
- Secure containerized environments by managing policies, hardening images, and monitoring incidents.
- Protect AI/ML models from attacks like data poisoning, model extraction, inversion, and jailbreaking.
- Apply encryption, access controls, anonymization, and de-identification to secure AI/ML pipelines.
- Collaborate across teams (Data Science, DevOps, IT Security) to embed security in MLOps.
- Lead security reviews, influence secure design decisions, and clearly communicate risks.
- Stay current on AI/ML threats, cloud innovations, and AI security research.
WHAT YOU'LL NEED:
- 5+ years in InfoSec, DevSecOps, or related roles, with experience securing AI/ML systems.
- Strong knowledge of OWASP for LLMs and NIST AI RMF; experience with tools like Snyk is a plus.
- Proficient in Python, with working knowledge of ML libraries like TensorFlow, PyTorch, or scikit-learn.
- Experience reviewing ML code, securing MLOps pipelines, and integrating security into CI/CD.
- Skilled in threat modeling and securing fast-moving development environments.
- Comfortable working with regulated data and implementing privacy protections (HIPAA, GDPR, CCPA).
- Familiar with Responsible AI practices like content filtering, bias mitigation, and model guardrails.
- Experience in Agile environments and fast-paced dev cycles.
- Strong communication skills, with the ability to explain security concepts to all audiences.
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What We Do
We are a team of dedicated clinical terminologists, data scientists, industry subject matter experts, and informaticists who helped facilitate the evolution from analogue to digital capture of clinical events, the precise code-mapping that simplifies complex workflows, and the translation of unstructured into structured data. We “wrote the digital dictionary” used in every major EHR, and we are leveraging clinical AI to generate insights that expand and deepen our impact across the healthcare ecosystem.
At the end of the day, we don’t make decisions for our clients. We provide them with the digital tools to enable sound decision-making.
Why Work With Us
We are building a clinical intelligence stack—medical ontology, human expertise, and AI—that makes data more useful and more powerful. By enhancing data’s structure, richness, and precision, we reduce noise and error, streamline complexity, and create clarity across the clinical information chain.
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