Head of Engineering, Adthena

• If you have the skills but don't meet every requirement, reach out – we'd love to explore how you could be a great fit!
• Proven leadership of multi-team engineering organisations (20+ engineers)
• Strong background in distributed systems, high-scale data pipelines, and ML model deployment
• Deep understanding of modern data stacks. e.g, Spark, data bricks, and cloud-native architectures
• Previous experience working with Data Science teams and understanding how machine learning models are delivered
• Strong grasp of TypeScript/React or at least modern front-end engineering environments
• Solid experience with DevOps practices: CI/CD pipelines, containerisation, orchestration, monitoring, and cloud infrastructure (AWS preferred)
• Experience running engineering organisations with multiple disciplines (backend, web, data, ML, QA, DevOps)
• Demonstrated ability to build high-performing teams and coach strong engineering managers
• Excellent judgment around trade-offs between delivery speed, tech debt, stability, and innovation
• Comfortable in a fast-paced SaaS environment with enterprise customers and high expectations for product reliability
• Outstanding communication: clear, concise, and effective with technical and non-technical stakeholders
• Highly organised with strong planning and prioritisation ability
• Bias for action with a pragmatic, problem-solving mindset
• Values transparency, collaboration, and developer happiness

Desirable

• Reporting to: Paul Felby, Chief Tech & Product Officer
• This role offers the opportunity to lead engineering at a company operating at the intersection of large-scale data, machine learning, and the rapid evolution of search
• Adthena works with some of the world’s largest brands to provide competitive intelligence across traditional search platforms and the emerging generation of LLM-driven search experiences, including Google, ChatGPT, Perplexity, and Gemini
• As Head of Engineering, you will be responsible for the technical execution behind a platform that processes vast volumes of search data, runs complex distributed computations, and delivers enterprise-grade insights used daily by global marketing teams
• The challenge is not greenfield experimentation, but building, scaling, and evolving systems that already matter and extending them into entirely new areas
• You will step into an organisation where AI is already part of how software gets built
• We were early adopters and are now a leading company in this space
• Engineering teams use AI day-to-day to write, review, and evolve code
• This role carries ownership of taking those practices further, setting standards, shaping ways of working, and helping define what effective AI-assisted development looks like at scale
• A significant part of the opportunity lies in shaping how Adthena expands competitive intelligence beyond Google into LLM-driven search platforms
• This involves leading the development of new systems that help enterprises understand visibility, competition, and opportunity in search experiences that are rapidly becoming mainstream
• GenAI is embedded throughout the product and platform, from analysing complex datasets, to backend verification and labelling workflows, to generating insights and dashboards for clients
• As Head of Engineering, you will play a key role in guiding how these capabilities are designed, operationalised, and scaled to deliver consistent, reliable value
• As Adthena continues to grow, this role is central to strengthening the engineering organisation, accelerating delivery, and ensuring the technical foundations support sustained innovation, high quality, and long-term scale
• Own the engineering roadmap execution for all products and platform capabilities
• Join architectural discussion regarding direction for distributed data processing, ML pipelines, and web application architecture
• Ensure scalable, reliable systems that can handle massive datasets and evolving ML workloads
• Champion engineering best practices (testing, observability, CI/CD, incident response, documentation)
• Establish predictable delivery processes across all teams, improving speed without sacrificing stability
• Implement measurable engineering KPIs such as cycle time, deployment frequency, MTTR, and platform SLAs
• Drive continuous improvement in release quality through QA automation and DevOps collaboration
• Lead and mentor direct reports; create a culture of ownership, accountability, and high performance
• Build an engineering organisation that scales. hiring, role definitions, and career paths
• Foster a healthy, collaborative environment that supports deep technical work and cross-team alignment
• Partner with Product to prioritise work, refine requirements, and ensure successful product delivery
• Work closely with Data Science/ML teams to bring research into production-grade systems
• Collaborate with DevOps/SRE on infrastructure strategy, cost optimisation, and operational reliability
• Contribute to the company-wide technology strategy alongside the CTO
• Identify opportunities to accelerate innovation through tooling, platform investments, or architectural change
• Manage engineering budgets, tooling spend, cloud infrastructure cost, and vendor relationships

• Start Date: ASAP