Chief Architect of Enterprise AI GRC (Governance, Risk, and Compliance)

Chief Architect – Enterprise AI Governance, Risk & (GRC)

Location: Copenhagen, Denmark (Hybrid / Supported)

Department: Enterprise &

Type: Full-Time, Executive

About CPH.AI

CPH.AI engineers production-grade Machine Learning, scalable Data Platforms, and deterministic Generative AI systems for enterprise organizations where reliability, low latency, and sovereignty are paramount. We bridge of academic AI research with mission-critical systems engineering. We reject superficial wrappers and checklists, focusing instead on grounded model evaluation, verifiable data provenance, and deterministic execution environments.

The

As the Chief Architect of Enterprise AI GRC, you will define and build the technical foundation of how sovereign, high-stakes organizations govern, de-risk, and operationalize artificial intelligence at scale.

This is not drafting or checklist-auditing . You are a systems and architect who operationalizes legal and mandates (including the EU AI Act, ISO/IEC 42001, and NIST AI RMF) into automated, auditable, and rigorous engineering controls. You will design guardrails, data lineage pipelines, model verification harnesses, and cryptographic audit fabrics embedded directly into our clients' distributed compute and CI/CD pipelines.

You will report directly to executive , act as the principal technical for our governance practice, and serve as an elite technical to C-suiteleadershipand board-level risk committees across Europe and North America.

Core Responsibilities1. GRC System Architecture & Technical Enforcement

• Architect automated compliance-as-code frameworks that translate regulatory directives (e.g., EU AI Act high-risk requirements, GDPR, NIS2) into deterministic software contracts and deployment gates.
• Design end-to-end data provenance and model lineage architectures across distributed Lakehouses (Apache Iceberg, Delta Lake) and artifact registries, ensuring immutable traceability from training tokens to inference outputs.
• Build scalable runtime evaluation and guardrail architectures for Generative AI and autonomous agent systems (context verification, deterministic tool sandboxing, prompt injection mitigation, and automated hallucination/drift scoring).
• Architect private, air-gapped, and confidential compute environments (utilizing AMD SEV-SNP, Intel TDX, and hardware security modules) to eliminate intellectual property leakage and training-data contamination.

2. Risk Modeling, Adversarial Verification & Evaluation

• Establish standardized enterprise testing methodologies for red-teaming, adversarial model penetration testing, jailbreak resistance, and data exfiltration vectors.
• Design quantitative evaluation metrics and continuous monitoring pipelines for concept drift, covariate shift, disparate impact, demographic parity, and calibration loss.
• Implement differential privacy, synthetic data validation, and cryptographic zero-knowledge proof protocols for high-sensitivity data collaboration.

3. Client Advisory & Strategic Leadership

• Serve as the lead external technical authority for Tier-1 enterprise clients (financial services, healthcare, defense, critical infrastructure, and telecommunications).
• Conduct forensic architectural audits of legacy and greenfield AI deployments, identifying technical debt, security vulnerabilities, and non-conformity risks.
• Guide client CTOs, Chief Risk Officers, and General Counsels through technical due diligence, conformity assessments, and technical documentation required for regulatory body filing.
• Represent CPH.AI in regulatory working groups, enterprise standards consortiums, and academic forums shaping the future of AI safety and verifiable computing.

Qualifications & Track RecordRequired Technical Foundations

• Education: M.Sc. or Ph.D. in Computer Science, Applied Mathematics, Machine Learning, Computer Engineering, or a strictly adjacent quantitative field.
• Architecture Experience: 10+ years of demonstrable experience in distributed systems architecture, enterprise software engineering, and large-scale data platforms.
• ML Engineering Depth: 5+ years of hands-on experience designing, training, fine-tuning, or optimizing deep learning and ML systems (PyTorch, modern Transformer architectures, high-performance inference engines such as vLLM or TensorRT-LLM).
• Data Platform Mastery: Deep architectural command of Lakehouse platforms (Databricks, Snowflake, Apache Iceberg), feature stores, message brokers (Kafka), and streaming analytics engines.
• Regulatory & Framework Fluency: Proven experience engineering systems against structured governance frameworks (EU AI Act, ISO/IEC 42001, NIST AI RMF 1.0, ISO 27001, SOC 2 Type II).
• Systems Mindset: Strong grasp of secure software design principles, API boundary enforcement, and containerized cloud-native environments (Kubernetes, Linux kernel primitives, eBPF, secure enclaves).

Differentiating Qualifications

• Prior experience acting as a Principal or Chief Architect within a global consulting firm, tier-one enterprise data platform, or frontier AI lab.
• Documented authorship of open-source frameworks, patents, or peer-reviewed research papers in model interpretability, mechanistic interpretability, adversarial robustness, or verifiable computing.
• Deep knowledge of hardware-accelerated privacy-preserving techniques (Confidential Computing on NVIDIA H100/B200, Homomorphic Encryption, or Secure Multi-Party Computation).
• Track record of defending high-risk algorithmic systems before formal regulatory bodies or national oversight authorities.

What We Offer

• Direct Influence on SOTA Deployments: Shape the architectural standards governing multi-billion-dollar enterprise platforms across Europe.
• Executive Compensation: Highly competitive executive salary, annual performance bonus, and meaningful equity participation.
• Elite Peer Group: Collaborate with distinguished practitioners, world-class researchers, and systems engineers committed to technical excellence without corporate bureaucracy.
• Location & Work Model: Flexible, trust-based hybrid model based out of our Copenhagen office, with executive travel across key enterprise hubs. Full relocation support provided for international candidates.