AI Data & Security Governance Engineer; MAD-BS

Position: AI Data & Security Governance Engineer (MAD-BS-OR)
Job Description POSITION: AI Data & Security Governance Engineer DIVISION:
Metrology and Analysis Systems Division (MAD)
COMPANY:
Hitachi High-Tech America, Inc. (“HTA”)

LOCATION:

Hillsboro, ORTRAVEL:
Up to 25% (domestically and internationally)
REMOTE WORK:
Hybrid (+50% Onsite) – Onsite 60% / Remote 40%
EXPECTED PAY RANGE

$134,476 - $184,905 annually

This pay range is for the position’s base pay only. This position may be eligible for other compensation including incentive pay and/or allowances. Candidates will receive additional information during the interview and selection process.

POSITION SUMMARY

As an AI Data & Security Governance Engineer (AIE) at HTA, you will build the technical guardrails that allow our distributed engineering and data science teams to innovate safely. Instead of just writing policies, the AIE will implement ‘governance as code.’ The AIE will design and deploy automated security controls, manage data access infrastructure, and integrate model evaluation and security checks directly into our CI/CD pipelines.

The AIE will work closely with HTA divisions to ensure that our data storage, LLM deployments, and application architecture remain secure, compliant, and highly performant.

PRIMARY RESPONSIBILITIES Data Security, Access & Infrastructure Security

• Automated Access Controls:
  Design, implement, and maintain granular Role-Based Access Control (RBAC) and identity management across our cloud infrastructure and internal tools
• Data Protection Pipelines:
  Build automated data masking, anonymization, and encryption mechanisms into data ingestion and processing pipelines
• Infrastructure Security:
  Secure distributed storage solutions and ensure secure configurations across compute instances and databases
• Cloud IAM hardening, secret management (e.g., Hashi Corp Vault, AWS Secrets Manager), and zero-trust data access patterns
• Secure vector database architecture (e.g., Milvus, Pinecone, pgvector) with tenant isolation and metadata-level filtering

AI/MLSecOps & Guardrail Implementation

• Generative AI Security:
  Engineer and deploy technical safeguards for large language models (e.g., Llama or similar architecture), including input/output filtering to prevent prompt injection and data leakage
• CI/CD Integration:
  Integrate automated security scanning, fairness/bias testing, and model performance evaluations directly into standard CI/CD deployment manuals
• Model Monitoring:
  Build telemetry and alerting systems to track model drift, anomalous API usage, and compliance adherence in real-time

Data Governance Infrastructure

• Metadata & Lineage:
  Develop automated processes to extract and catalog metadata, ensuring end-to-end data lineage is tracked programmatically
• Audit Automation:
  Build automated reporting scripts and dashboards to provide continuous visibility into data access logs and model compliance for security audits

• Other duties as assigned

EDUCATION, LICENSES, and/or CERTIFICATION REQUIREMENTS

• Master’s degree in Computer Security, AI Engineering/Governance, Software Engineering, or related field or equivalent combination of education and experience

EXPERIENCE and TRAVEL REQUIREMENTS Technical Experience

• Minimum of five (5) years of software, data, or security engineering experience
• Minimum of five (5) years of experience of programming proficiency in Python, SQL, Bash, Go, or similar languages used in data and infrastructure engineering
• Minimum of five (5) years of experience with AI/ML Ops deploying and securing machine learning models (including generative AI/LLMs) in production environments
• Minimum of five (5) years of experience with Dev Ops & Automation CI/CD pipelines, Git workflows (e.g., monorepo architecture), and infrastructure-as-code tools
• Minimum of five (5) years of experience in Governance…