Head of Engineering

Help us use technology to make a big green dent in the universe!

Kraken powers some of the most innovative global developments in energy. We’re a technology company focused on creating a smart, sustainable energy system. From optimising renewable generation, creating a more intelligent grid, and enabling utilities to provide excellent customer experiences, our operating system for energy is transforming the industry around the world in a way that benefits everyone.

As Head of Engineering for Data, ML & AI Tools, your main responsibility will be to lead multiple high-impact teams building AI-powered tools, voice interfaces, analytics products, and machine learning models that support utility clients and internal teams. You'll manage a group of Engineering Leads and collaborate closely with cross‑functional teams to define technical strategy, deliver production‑grade systems, and drive innovation across LLM, data, and ML domains.

Your teams will be responsible for delivering agent‑assist tools like Answer Bots, customer‑facing Voice Bots, predictive models for utility use cases (e.g., water leakage detection, churn), and client dashboards that turn data into actionable insights.

• Lead and scale our cross‑functional Engineering, ML and data engineering teams, including machine learning engineers, LLM/AI engineers, data analysts, and software engineers
• Drive the development of intelligent tools for customer agents (e.g., LLM-based Answer Bots) and end‑users (e.g., Voice Bots) that improve service efficiency and experience
• Guide the team delivering predictive ML models for utility clients in areas like water leak detection and churn prediction, ensuring robustness, explainability, and client value
• Oversee the development of data analytics products – including dashboards and data pipelines – that deliver actionable intelligence to utility clients
• Set the long‑term technical vision for our AI & analytics products while being hands‑on in system design, architecture reviews, and high‑impact technical decisions
• Partner closely with cross‑functional stakeholders, including product managers, customer teams, and delivery leads, to align technical solutions with business goals
• Champion experimentation, prototyping, and fast iteration to explore new use cases with GenAI and classic ML across business domains
• Build systems that combine structured data, unstructured customer interactions, and real‑time operational signals, powering the next generation of intelligent decision support
• Stay on the forefront of emerging technologies in LLMs, RAG, reinforcement learning, and agentic workflows – and translate them into practical, scalable products

• Proven leadership experience in managing multi‑disciplinary engineering teams (20+ engineers), including ML, LLM, data engineering, and platform engineering
• Understanding of ML lifecycle – from data ingestion and feature engineering to model training, evaluation, and deployment in production
• Hands‑on experience deploying LLM‑based systems (e.g., RAG pipelines, tool calling, fine‑tuning, RLHF) and integrating them into real‑world applications
• Experience developing customer‑facing AI tools, voice‑based interfaces, or agent augmentation systems is highly desirable
• Strong architectural skills and the ability to make pragmatic decisions between prototypes and production‑grade systems
• Experience building and operating robust data pipelines, ETL frameworks, and analytics dashboards that serve clients in regulated industries like water or telco
• Familiarity with modern AI/ML stacks:
  Python, Kubernetes, PyTorch, Lang Chain, vector databases, etc
• Demonstrated ability to align AI and analytics initiatives with business outcomes and customer value
• Inspirational leadership style with a strong product sense and ability to lead through ambiguity. Experience managing teams of teams (20+ engineers) is desired

Kraken is a certified Great Place to Work in France, Germany, Spain, Japan and Australia. In the UK we are one of the Best Workplaces on Glassdoor with a score of 4.7. Check out our Welcome to the Jungle site (FR/EN) to learn more…