Director – AI Engineering
GBP 98K-250K (estimate) Executive-level Contract
Tasks
- Apply FinOps for token and cloud cost management
- Build agentic systems across service delivery digital products and productivity
- Build and lead AI engineering and data science team
- Co-own AI use case prioritization and roadmap
- Define AI engineering deployment and testing standards
- Deliver enterprise document extraction platforms
- Engineer digital integrated agents
- Ensure AI systems are auditable and evidenced
- Ensure measurable operational ROI for AI deployments
- Evaluate third party embedded AI agents
- Horizon scan frontier model and agent development
- Implement security resilience and regulatory controls
- Lead AI/ML model development and deployment
- Migrate agent workloads to Claude stack
- Operate within AI governance and model risk framework
- Own MCP enabled agentic platform architecture
- Ship function specific AI agents
- Upskill teams in AI and agentic workflow delivery
Perks/Benefits
Skills/Tech-stack
APIs | Agent workflows | Agentic Engineering | Anthropic SDK | Artificial Intelligence | Audit trails | CI/CD | Claude | Claude Code | Cloud Computing | Cloud Cost Management | Context engineering | Conversational Analytics | Cost Management | Data Pipelines | Document extraction | Enterprise Software | Enterprise software integration | Evaluation Frameworks | Explainability | FinOps | Human-in-the-loop | Language Models | Large Language Models | MCP | Machine Learning | Multi-Agent | Multi-agent workflows | Prompt engineering | Responsible AI | Retrieval-Augmented Generation | Software integration | The Loop | Token Cost | Token Cost Management | Tool orchestration | Unit economics | Usage monitoring | Workflow automation
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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