AI Integrity Engineer

About Premera Blue Cross

Our purpose at Premera Blue Cross is to improve customers’ lives by making healthcare work better. We are committed to being a workplace where employees are empowered to grow, innovate, and lead with purpose. This commitment has earned us recognition as one of the best companies to work for, fostering a culture of collaboration and continuous development. Learn more about how Premera supports our members, customers, and communities through our Healthsource blog.

The Opportunity: AI Integrity Engineer

We are seeking an AI Integrity Engineer to strengthen security across Premera’s evolving AI, Cloud, and Data ecosystems. This telecommuter role partners with Enterprise Engineering to architect and secure modern application and infrastructure environments. By bridging Platform Engineering and AI Security, you will lead the development of secure AI pipelines, agentic workflows, and robust data warehouse protections. You’ll work cross-functionally to build scalable, resilient foundations that embed AI-specific guardrails directly into the enterprise fabric.

This is a hands-on contributor role supporting teams building AI services by establishing secure identity, access, guardrails, and lifecycle controls for autonomous and semi-autonomous AI agents. This position may be hired at a Level III or IV, depending upon experience.

What You'll Do

Application Security:

• SAST & DAST Implementation: Design and manage Static and Dynamic Application Security Testing pipelines to detect security flaws early in the lifecycle.
• Vulnerability Remediation: Lead regular vulnerability scans of codebases and containers, analyze results, prioritize critical issues, and partner with engineering teams to drive remediation.
• Secure Supply Chain: Manage artifact security and dependency scanning using Artifact and Dependency Scanning tools.

AI Security & Governance:

• Protect AI Assets: Secure data pipelines, models, and agents from threats such as prompt injection, model hijacking, data-poisoning, and trojaned instructions.
• Secure RAG Pipelines: Enforce retrieval integrity, document ingestion safety, and data-access controls to prevent indirect prompt injection and data leakage.
• Secure Interaction: Enable secure agent-tool interaction using frameworks such as MCP by implementing strong authentication, authorization, and scoped tool-permission boundaries.
• Guardrails & Safety: Deploy and maintain AI guardrails, including safety filters, task adherence controls, scoped action permissions, and prompt-shielding mechanisms.
• Threat Modeling: Perform AI-specific threat modeling focused on jailbreaks, adversarial inputs, indirect prompt attacks, and non-deterministic system behavior.
• Compliance: Support cross-team compliance efforts by ensuring audit trails, usage governance, and adherence to emerging AI control frameworks.

AI Identity, Access & Authentication:

• Implement identity governance frameworks tailored for AI agents, such as ephemeral authentication, attribute-based access control (ABAC), and just-in-time provisioning.
• Manage M2M/OIDC/OAuth identity configurations for per-application agent authentication, including scopes, claims, client credentials, and automated key/secret rotation.
• Configure Azure Entra Agent IDs (or similar) to issue trackable, short-lived identities for unique agents.
• Implement governance around credential lifecycle, preventing agent credential sprawl.

Secure Agent Tooling & Workflow Controls:

• Administer and maintain the MCP Registry or equivalent systems to govern secure access to tools and APIs for agent workflows.
• Monitor and govern agent tool selection, ensuring safe invocation boundaries and preventing privilege escalation within automated workflows.
• Support controlled integration of agents with internal services without owning traditional infrastructure security functions (e.g., firewall administration, IDS/IPS tuning).

Data Protection & Observability:

• Implement PII detection, redaction workflows, and DLP controls natively within agentic systems.
• Maintain auditability for agent actions, identity transitions, tool use, and retrieval events.
• Monitor AI-related logs, security signals, and performance anomalies; support anomaly detection without requiring deep SIEM engineering or incident-response forensics.

Platform & Infrastructure (AI-Focused Support Only):

• Support secure configuration of AI Gateways for model routing, rate-limiting, tenant isolation, and guardrail policy execution.
• Support IaC-based configuration reviews for AI workloads without owning broad enterprise infrastructure hardening.

What You'll Bring

Required Qualifications:

• Bachelor's Degree in Computer Science, Statistics, Mathematics, or a related field; or 2+ years of experience in a related, professional IT/analytics position.
• Level III: (3) years of industry experience in developing, deploying, and maintaining AI or ML systems. Up to two years of industry experience may be substituted with an AI-centered master’s/PhD degree or AI Engineering certifications.
• Level IV: (5) years of industry experience in developing, deploying, and maintaining AI or ML systems. Up to two years of industry experience may be substituted with an AI-centered master’s/PhD degree or AI Engineering certifications.

Preferred Qualifications:

• Experience securing data within Data Warehouse Platform environments.
• Proficiency with Cloud Provider DevOps Platform for CI/CD pipelines and board management.
• CISSP, GIAC, GSEC, and/or SSCP security certification (or ability to obtain).
• Experience with ABAC, ephemeral identity, OIDC/OAuth, and JIT access provisioning for automated workloads.
• Familiarity with AI agent frameworks, guardrails, RAG patterns, and AI-specific risks.
• MCP or similar tool-registry configuration experience.
• Understanding of AI orchestration, agentic system architectures, and secure agent workflow design.
• Experience implementing AI-specific DLP, prompt-shielding, and PII-detection controls.
• Identity security, DevSecOps, or platform-security support.
• IAM, access governance, security automation, or comparable disciplines.

Knowledge, Skills, And Abilities:

• Strong conceptual reasoning about AI-specific risks and emergent behaviors.
• Ability to translate AI safety and security requirements into actionable guidance for engineering teams.
• Excellent communication and collaboration across cross-functional teams.
• Commitment to responsible, secure AI adoption.
• Proficient at ethical AI practices including explainable AI, fairness, and mitigation of bias/hallucinations.
• Strong mentorship skills.
• Ability to articulate the technical details and tradeoffs of AI solutions to non-technical stakeholders in a clear and concise manner.

Total Rewards & Benefits

Premera offers a comprehensive total rewards package, including medical, vision, and dental coverage with low employee premiums, voluntary benefits, life and disability insurance, and retirement programs (401K employer match and pension plan). We also provide wellness incentives, generous paid time off, tuition assistance, and an employee recognition program. For hybrid employees, on-campus perks include free parking, subsidized cafes, a fitness & well-being center, and engaging activities.

Key skills/competency

• AI Security
• Application Security
• Data Protection
• Identity Governance
• Access Control
• Threat Modeling
• Vulnerability Management
• Compliance
• Secure AI Pipelines
• DevSecOps