Senior Software Engineer, AI Governance

Natera

. Design, build, and own the guardrail layer inside Natera's LLM Gateway, including content filtering, output validation, PHI/PII detection, prompt injection defenses, session retention, and audit logging .

Posted 9/23/2026full-timeRemote • United StatesSenior💰 $125,000 - $156,300 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI governance and risk management, with a strong focus on compliance with HIPAA and NIST AI RMF. Proficient in building and maintaining production AI systems, including LLM infrastructure and observability tools.

Highest-signal resume keywords

AI Governance EngineeringProduction AI Systems DevelopmentPython ProgrammingHIPAA ComplianceML Observability and Monitoring

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Hard Skills

AI Risk ManagementLLM InfrastructureData Pipeline DevelopmentAPI-Level IntegrationsRisk-Based Output RoutingContent FilteringOutput ValidationModel Drift DetectionPrompt Injection DefensesTechnical Documentation Writing

Soft Skills

CollaborationAdvisory SkillsCommunication

Tools & Technologies

ArizeFiddlerWhylogsAI Incident Response ToolingMonitoring Infrastructure

Certifications & Qualifications

CIPPCIPTResponsible AI Credentials

Industry Keywords

HealthcareLife SciencesFinancial ServicesPHI/PII Data HandlingRegulated EnvironmentNIST AI RMFISO 42001AI Acceptable-Use Policy

Tech Stack

Tools & technologies

ChaiPython

About the role

Key responsibilities & impact

Design, build, and own the guardrail layer inside Natera's LLM Gateway, including content filtering, output validation, PHI/PII detection, prompt injection defenses, session retention, and audit logging
Engineer governance controls for agentic runtime and RAG infrastructure, including policy enforcement hooks, risk-based output routing, retrieval filtering, citation integrity checks, and PHI exposure prevention
Instrument platform controls with observability for filtering, flagging, escalation, and risk-profile drift
Ensure AI platform controls meet HIPAA, RAQA, and Natera data classification requirements at design time
Design and implement automated AI risk intake, scoring, tiering, and review-path routing aligned to NIST AI RMF, CHAI, and the EU AI Act
Build and maintain an auditable AI Risk Register
Build monitoring for production AI use cases, including accuracy tracking, drift detection, misuse alerting, and escalation thresholds
Build and maintain AI incident response tooling for detection, alert routing, decision logging, and remediation tracking
Run AI use-case intake and evaluate new use cases against the risk-tiering model
Facilitate high-risk use-case reviews with the AI Governance Board and produce recommendations and controls
Maintain risk questionnaires, scoring rubrics, and tiering criteria
Own technical due diligence for AI vendors and foundation model providers
Maintain vendor AI risk assessment frameworks and AI-specific contractual controls
Help write and maintain Natera's AI acceptable-use policy
Advise teams on practical engineering requirements for AI governance
Report to the Head of AI & Data Governance and collaborate with platform engineering, Legal, Privacy, RAQA, and business teams

Requirements

What you’ll need

7+ years of software engineering experience, including at least 3 years working directly in AI/ML systems, LLM infrastructure, or AI safety and governance engineering
Hands-on experience building production AI systems, including LLM pipelines, RAG architectures, agentic runtimes, or AI observability and monitoring infrastructure
Practical understanding of production LLM risks, including hallucination, bias, prompt injection, data leakage, and model drift, with experience building technical mitigations
Proficiency in Python and experience building API-level integrations, middleware, and production data pipelines
Experience with ML observability and monitoring, including model instrumentation, drift thresholds, and alerting
Experience in a regulated environment such as healthcare, life sciences, or financial services, with HIPAA or equivalent compliance obligations and hands-on PHI/PII data handling
Working knowledge of NIST AI Risk Management Framework (AI RMF 1.0) or ISO 42001, applied through implementation of controls
Ability to write technical specifications and documentation for engineers and Legal
Nice to have: LLM gateway architectures, RAG pipeline controls, content moderation systems, or agentic AI safety infrastructure
Nice to have: AI red-teaming, adversarial testing, or structured model evaluation
Nice to have: Trust and safety infrastructure or ML monitoring platforms such as Arize, Fiddler, Whylogs, or similar
Nice to have: Diagnostics, genomics, or clinical AI experience
Nice to have: HIPAA, FDA GxP, CLIA, PMDA, or GDPR-compliant systems experience
Nice to have: CIPP, CIPT, or recognized Responsible AI credentials

Benefits

Comp & perks

Comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents
Free testing for employees and immediate families
Fertility care benefits
Pregnancy and baby bonding leave
401(k) benefits
Commuter benefits
Employee referral program