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Director of Data Engineering & AI
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Director of Data Engineering: AI & Data Platforms
Location: London (Hybrid – 1–2 days per week onsite)
Salary: Up to £160,000 + equity & benefits
Reports to: CTO
Overview of the Role
This is a rare opportunity to shape and lead the evolution of a next-generation, AI-native data platform within a high-growth, well-funded scale-up.
As Director of Data Engineering, you will operate at the intersection of strategy and execution—partnering closely with the CTO to define the long-term architecture, build a high-performing team, and transition the organisation from a traditional data platform to an agentic, AI-driven ecosystem.
You will inherit a capable team, but more importantly, you will define its future: how it scales, what it builds, and where it leverages external innovation. This role combines hands-on technical leadership (circa 50%) with team and organisational leadership (circa 50%), making it ideal for a builder-leader who thrives on both architecture and people.
Key Responsibilities
Strategic Leadership & Platform Vision
- Partner with the CTO to define and execute the AI and data platform strategy, including critical build vs buy decisions
- Establish a clear approach to partner vs upskill, ensuring the team leverages external innovation while building core internal capability
- Shape the long-term vision for an agentic, AI-native data ecosystem
AI-Driven Data Platform Development
- Lead the design of a unified AI search layer, combining vector, keyword, and graph-based approaches (e.g. GraphRAG)
- Architect and scale agent-based systems and human-in-the-loop workflows
- Oversee the development of a knowledge graph and data enrichment pipelines to unlock proprietary data value
- Drive AI/ML Ops maturity, including LLM deployment, RAG pipelines, and evaluation frameworks
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Engineering & Architecture
- Define scalable, cloud-native architectures across GCP (preferred) and AWS
- Lead cross-cloud data orchestration, ensuring seamless data flow from ingestion to intelligence layers
- Guide technical decisions on tooling, frameworks, and platform evolution
Team Leadership & Growth
- Lead and develop a team of data and AI engineers, including senior and staff-level contributors
- Build a culture of engineering excellence, accountability, and continuous improvement
- Hire, mentor, and scale the team in line with business growth
Delivery & Impact
- Ensure engineering effort is focused on high-value, domain-specific problems
- Improve velocity through modern engineering practices and AI-assisted development
- Balance innovation with pragmatism—avoiding unnecessary reinvention while maintaining competitive advantage
Key Requirements
Leadership & Experience
- Proven experience as a Director or Senior Engineering Manager leading data/platform teams
- Strong track record of scaling teams and mentoring engineers (typically 5+ years in leadership roles)
- Comfortable operating in a hands-on leadership capacity
Data Platform & Cloud Expertise
- Experience building and scaling high-volume data platforms
- Strong knowledge of GCP (BigQuery preferred) and exposure to AWS
- Expertise in data pipelines, distributed processing, and Python-based data services
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AI & Emerging Technologies
- Exposure to or strong interest in agentic systems, LLMs, and AI-driven architectures
- Experience with AI search (vector databases, hybrid search, GraphRAG) is highly desirable
- Familiarity with knowledge graphs, ontologies, or complex data modelling
Strategic & Commercial Thinking
- Experience making build vs buy and technology investment decisions
- Ability to evaluate and integrate third-party tools, platforms, and partnerships
- Strong alignment with business outcomes, not just technical delivery
Additional Information
- Working Pattern: Hybrid (1–2 days per week in London office)
- Salary: Up to £160,000 + equity + benefits (private healthcare, pension)
- Team Size: ~4–5 engineers currently, scaling further
- Career Progression: Clear path towards VP Engineering / CTO
- Environment:
- Stable, well-funded scale-up (not early-stage chaos)
- Highly unique, proprietary datasets
- Strong investment in modern AI tooling and practices
Interview Process (3 Stages)
- Introductory conversation with senior leadership
- Technical/design interview (architecture-focused)
- Final interview with executive stakeholders (in-person)
This role is ideal for a senior engineering leader who wants to build, shape, and scale not just maintain. If you’re motivated by cutting-edge AI, complex data challenges, and genuine strategic influence, this is an opportunity to make a lasting impact.
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