About this role
Summary: Lead the design, architecture, and evolution of ENSEK's AI/ML Platform as a founding technical lead. Define technical standards, build MLOps/LLMOps capabilities, and mentor engineers to enable product teams to safely deploy Machine Learning and Generative AI solutions at scale.
About ENSEK
ENSEK builds the cloud‑native SaaS software that’s transforming how energy retailers operate, innovate and manage at scale.
We help retailers lower operating costs, improve billing accuracy for consumers, and enhance customer experience through automation and AI‑driven insight, all underpinned by modern, cloud‑native architecture.
ENSEK is at an exciting inflection point as we scale at pace towards new international horizons. If you’re driven by solving complex, real‑world problems and want to build modern technology that accelerates the global energy transition, you’ll feel right at home with us.
##### About the role
We're looking for a Staff AI/ML Engineer to become the founding technical lead for ENSEK's AI/ML Platform.
This is a unique opportunity to shape a new strategic capability from the ground up. You'll lead the design, architecture and evolution of the shared platform that enables product teams across ENSEK to safely build, deploy and operate Machine Learning, Generative AI and Agentic AI solutions at scale.
Working closely with Data Scientists, Platform Engineers and Data Engineers, you'll define the technical direction, standards and golden paths that allow teams to move from experimentation to production with confidence. You'll also play a key role in building the team, culture and operating model that will support AI innovation across the organisation for years to come.
##### Key responsibilities:
As a Staff AI/ML Engineer, you will:
- Lead the architecture, technical strategy and roadmap for ENSEK's AI/ML Platform, evolving it into a scalable capability used across multiple product domains.
- Design and build production-ready golden paths for Machine Learning, GenAI and Agentic AI solutions.
- Establish standards for model lifecycle management, prompt versioning, deployment, serving, retrieval-augmented generation (RAG), orchestration and secure tool access.
- Build robust MLOps and LLMOps capabilities, including evaluation frameworks, experimentation tooling, observability, monitoring and cost management.
- Create and maintain registries for AI products, models and prompts to ensure visibility, governance and operational excellence.
- Partner closely with Data Scientists to operationalise machine learning models, GenAI applications and agentic workflows into reliable production services.
- Define patterns for human-in-the-loop workflows, confidence-based routing and AI safety mechanisms.
- Embed security, governance, compliance and responsible AI practices into the platform from day one.
- Collaborate with Legal, Cyber Security, Risk and Product teams to ensure AI solutions remain safe, explainable and auditable within regulated environments.
- Mentor ML Engineers and other developers across the organisation while helping establish engineering standards and best practices.
- Contribute to the long-term growth, structure and operating model of ENSEK's AI Engineering capability.
##### Key outcomes:
You'll know you're making an impact when:
- The platform's first AI-powered capabilities are running successfully in production and delivering measurable business value.
- Multiple product teams are building, deploying and operating AI solutions through the platform's approved patterns and tooling.
- AI products are consistently governed, observable and measurable through standardised evaluation, monitoring and reporting.
- Every production AI capability is registered, auditable and supported by appropriate safety guardrails.
- Teams have clear guidance on model selection, hosting approaches and platform capabilities.
- The platform becomes the preferred route for AI innovation across ENSEK rather than teams developing isolated solutions.
- A high-performing ML Engineering team is established with strong engineering practices and a close partnership with Data Science.
##### Experience required:
We're seeking an experienced technical leader who combines strong software engineering fundamentals with deep expertise in modern AI and Machine Learning platforms.
You'll bring:
- Significant experience as an AI Engineer, ML Engineer, Software Engineer or Technical Lead delivering production Machine Learning and AI solutions.
- Experience operating at Staff Engineer, Principal Engineer or equivalent technical leadership level.
- Deep expertise in MLOps and production machine learning platforms, including model deployment, serving, monitoring, evaluation and lifecycle management.
- Proven experience building and operating applications powered by Large Language Models (LLMs).
- Strong hands-on experience with Retrieval-Augmented Generation (RAG), prompt engineering, evaluation frameworks and agentic AI workflows.
- Excellent software engineering skills, ideally in Python, alongside experience designing distributed systems and production services.
- Experience building and operating cloud-native services on AWS using containers, Kubernetes, Infrastructure as Code and CI/CD practices.
- Strong understanding of platform engineering principles, developer experience and self-service platform design.
- Experience implementing AI governance, model safety, privacy controls and responsible AI practices.
- The ability to make pragmatic technical decisions while balancing performance, cost, scalability and risk.
- Excellent communication and stakeholder management skills, with the ability to explain technical concepts and trade-offs to both technical and non-technical audiences.
##### Nice to have
- Experience with MCP (Model Context Protocol) or similar emerging standards.
- Experience building enterprise AI platforms supporting multiple product teams.
- Experience with lakehouse data platforms and data engineering ecosystems.
- Knowledge of regulated industries such as Energy, Utilities, Financial Services or Healthcare.
- Experience working with Agentic AI architectures and tool-using AI systems.
- Familiarity with emerging AI observability, evaluation and governance tooling.
##### Company Benefits
- 25 days’ holiday + bank holidays
- Option to buy or sell 5 extra annual leave days per year
- Vitality Health Insurance, including private healthcare, virtual GP access, mental‑health support and wellbeing perks (50% off gym memberships -Virgin Active, Nuffield, PureGym)
- Pension with 5% matched contribution
- Regular team‑wide and company‑wide events
- 2 volunteering days per year to give back
- Remote‑first working environment with offices in London and Nottingham