Overview
We develop enterprise software that applies AI to energy efficiency and carbon/ESG management. Our products help organizations improve operational performance, reduce consumption and emissions, and meet reporting obligations. This role suits an engineer who enjoys building reliable data-driven systems and wants their work to contribute to measurable decarbonization outcomes.
Purpose of the role
The AI Software Engineer will build platform capabilities that enable data-driven insights and reporting for organizations pursuing energy efficiency and carbon reduction. The work spans data services, analytics features, and integration points used by internal teams and downstream systems. (Detailed product mechanics are discussed during interviews.)
Key responsibilities
- Data services & integrations: Design, implement, and maintain secure data ingestion and transformation services that connect to external monitoring and enterprise systems via well-defined APIs.
- Analytics features: Implement modular analytics and machine-learning components for issue detection, performance assessment, and optimization; version and document these components for reuse.
- Outputs & interfaces: Define consistent output contracts (metrics, recommendations, reporting artefacts) to ensure downstream users and systems can consume results reliably.
- Reliability & operations: Ensure services are observable, well-tested, and resilient; contribute to runbooks and operational dashboards as the platform scales.
- Collaboration & documentation: Translate domain requirements into technical designs; participate in design reviews; produce clear documentation for architecture, workflows, and interfaces.
- Security & governance: Apply appropriate data governance practices for regulated environments, including access control, auditability, and data quality.
Candidate profile
Essential
- Strong software engineering background (Python preferred).
- Hands-on experience building data processing systems (batch and/or streaming) and integrating with external systems via REST/GraphQL.
- Practical familiarity with ML libraries and time-series or event data.
- Proficiency with testing, CI/CD, containers, and a major cloud platform.
- Clear communication and the ability to work effectively with product, data, and domain specialists.
Advantageous
- Experience in energy, sustainability, industrial operations, or other asset-intensive domains.
- Exposure to MLOps (model training pipelines, monitoring, lifecycle management).
- Awareness of data privacy and reporting considerations relevant to ESG/carbon disclosures.
What we offer
- Competitive compensation aligned to experience and impact.
- Employee share options for eligible team members.
- A clear path into senior technical leadership as the platform expands.
- The opportunity to apply advanced data and AI techniques to tangible energy and carbon-reduction outcomes.
How to apply
Please apply via LinkedIn or email your rsum to [Confidential Information] and a short note describing a data/ML system you have delivered end-to-end. Shortlisted candidates will be invited to a technical discussion and a practical exercise.
