About the project
We are seeking an experienced Enterprise AI & Governance Architect to define and drive our organization-wide AI architecture, technical standards, governance framework, and adoption strategy.
This role sits at the intersection of Enterprise Architecture, AI/GenAI, Software Engineering, Cloud, Security, Data Architecture, and AI Governance. You will establish AI as a secure, scalable, governed, and auditable enterprise capability, ensuring that AI solutions are designed, deployed, operated, and monitored according to consistent architectural and governance principles.
Working closely with the AI Officer, Enterprise Architects, Cybersecurity, Engineering, Data, Legal/Compliance, and business stakeholders, you will translate business objectives, regulatory requirements, and organizational policies into practical technical standards and governance mechanisms.
Your responsibilities
- Define and evolve the organization's AI strategy and target architecture.
- Establish AI governance, architecture standards, approval processes, and lifecycle controls.
- Design reference architectures for Generative AI, RAG, AI Agents, Machine Learning, and enterprise knowledge systems.
- Define AI platform architecture, including model management, observability, guardrails, security, and governance tooling.
- Integrate AI into the full Software Development Lifecycle (SDLC).
- Develop architecture and standards for MLOps, LLMOps, model lifecycle management, and AI operations.
- Define AI security architecture and technical controls in collaboration with Cybersecurity teams.
- Establish enterprise approaches for AI data, knowledge, RAG, vector search, and information access.
- Ensure compliance with frameworks including the EU AI Act, ISO 42001, ISO 23894, ISO 27001, NIST AI RMF, GDPR, and relevant engineering standards.
- Drive the transition of AI initiatives from proof of concept to scalable enterprise capabilities.
Our requirements
- Proven experience in Enterprise, Solution, Software, or Cloud Architecture.
- Strong understanding of enterprise software systems and the full SDLC.
- Practical experience with AI/ML/GenAI architectures.
- Experience translating governance, risk, and compliance requirements into technical controls and standards.
- Strong knowledge of security architecture, IAM, integrations, and distributed systems.
- Experience with cloud, on-premises, or hybrid environments.
- Ability to work across multiple teams and organizational functions.
- Experience with MLOps/LLMOps.
- Enterprise RAG and knowledge architecture experience.
- AI model and platform governance experience.
- Experience in regulated, high-assurance, aerospace, defense, or engineering environments.
- Familiarity with ESA, ECSS, or comparable engineering standards.
Benefity
Technical Skills. Experience in several of the following areas:
- Enterprise Architecture.
- AI/ML and Generative AI.
- Python and modern programming languages.
- APIs and distributed systems.
- Microservices.
- Containers and Kubernetes.
- CI/CD.
- Cloud platforms.
- Databases.
- IAM and security architectures.
- Infrastructure automation.
- Monitoring and observability.
- RAG, embeddings, vector databases.
- AI agents and tool orchestration.