Lead AI Architect – Build PA's AI Capability

About the role

PA Consulting is building its AI capability team in Copenhagen and is looking for a Lead AI Architect to act as its technical centre of gravity. You will set the technical direction for designing and delivering enterprise AI solutions to clients, taking architecture from the whiteboard into production. The role suits someone deeply curious about technology and able to explain architecture decisions to executive teams in terms of risk, cost, speed and competitive advantage.

Key responsibilities

• Own the technical vision of the AI capability team and define reference architectures, reusable patterns and technical standards.
• Track the AI landscape (models, frameworks, tooling, infrastructure) and decide what to adopt, test or ignore.
• Build accelerators, reusable components and demos that speed up delivery and strengthen proposals.
• Architect and build end-to-end enterprise AI solutions, from data integration and retrieval to model orchestration, agentic workflows, security and operations, moving from proof of concept to production systems.
• Design multi-agent systems, tool-using agents and human-in-the-loop workflows, with unified data access, institutional memory and knowledge reuse.
• Put evaluation, observability, guardrails and cost control in place from day one.
• Advise CxOs, CIOs and CTOs on architecture choices such as build vs. buy, cloud vs. sovereign, and support business development through solutioning and proposals.
• Mentor engineers, data scientists and consultants, and collaborate with Jacobs' engineers and international AI experts.

Required profile

• Extensive hands-on experience architecting AI, data or software solutions in enterprise settings, as architect, principal engineer, tech lead or CTO.
• Fluent English and Danish.
• Plus: consulting or client-facing advisory experience, experience in regulated industries, experience building and leading technical teams, and public contributions such as open-source work or talks.

Required skills

• Modern AI engineering: LLMs, prompt and context engineering, fine-tuning, RAG, vector databases, knowledge graphs, agentic frameworks, Ops and MLOps, evaluation and AI security.
• Cloud and data platforms: Azure, AWS or GCP, and tools such as Databricks, Snowflake or Microsoft Fabric.
• Software engineering in Python and/or TypeScript.
• Enterprise architecture, integration, identity and security; responsible AI, the EU AI Act, GDPR and data sovereignty.

To apply, send your CV and a short note about something you've built that you're proud of; applications are reviewed on an ongoing basis.