Head of Software Engineering - Energy Trading & BESS Optimisation in London

Private Equity Backed European Renewable Energy Platform - Battery Storage, Solar & Wind

Location: London/Europe (Flexible)

The role involves architecting, scaling, and delivering a next-generation software platform for European grid-scale BESS trading. The Head of Software Engineering will bridge the gap between high-frequency hardware telemetry, real-time wholesale electricity market trading, complex Machine Learning (ML) workflows, and modern software paradigms. The role is crucial in pioneering agentic, spec-driven development practices to enhance engineering velocity, maintain high software quality, and define the future of energy tech infrastructure.

Key Tasks and Responsibilities

• Engineering & Architecture Leadership: Recruit, lead and mentor a cross-functional Software Engineering and MLOps team. Own the technical roadmap and architecture, aligning software capability with market expansion across key European power markets and TSO services.
• AI-Native & Agentic Engineering Pipeline Development: Define and implement graph-based agentic, spec-driven software engineering delivery pipeline. Institutionalize the use of agentic coding platforms (such as Claude Code and custom agentic CI/CD loops) to transform how code is written, reviewed, secured, tested, and deployed. Establish rigorous specification design standards (executable specifications, MCP servers, Architecture-as-Code) that allow AI agents to reliably generate, refactor, and maintain production-grade codebase.
• Real-Time Wholesale Trading & Dispatch Systems: Oversee the design and execution of reliable, low-latency automated trading and dispatch pipelines connecting automated bidding strategies to physical assets. Work with Data Scientists to productionise price forecasting and real-time asset-backed optimisation capabilities.
• IoT Telemetry & Edge-to-Cloud Systems: Architect cloud-native IoT ingestion pipelines capable of ingesting high-frequency telemetry from geographically distributed BESS assets via industrial protocols (Modbus, MQTT). Design high-availability and bi-directional control reliability between cloud optimization engines and site-level edge controllers.
• Enterprise Data Lakehouse & ML Infrastructure: Lead the architectural design of our core enterprise Data Lakehouse on Databricks using Medallion principles. Build robust pipelines for feature generation, enabling real-time ML inference for BESS modeling, price forecasting, and automated bid optimization.

Skills and Experience

• Required Qualifications & Experience:
• Engineering & Product Leadership: 8+ years of total software engineering experience, with at least 3+ years in senior leadership (Director, Head of, or VP level) directly managing software engineering teams.
• Energy & Trading Domain Expertise: Proven track record building or scaling software platforms in wholesale real-time electricity trading, algorithmic order book management, or flexible asset optimization (virtual power plants, BESS, renewable generation). Strong familiarity with European market structures (intraday continuous, day-ahead, ancillary services).
• Agentic & AI-Native Development: Practical, hands-on experience implementing agentic spec-driven development workflows. Strong familiarity with LLM coding infrastructure (e.g., Claude Code, automated context management, custom agent loops, LangGraph).
• Cloud Architecture & Infrastructure: Deep expertise in public cloud architecture (AWS, Azure, or GCP), serverless event-driven design, containerization (Kubernetes), and infrastructure-as-code (Terraform).
• IoT & Industrial Data Ingestion: Proven experience designing high-throughput IoT streaming pipelines for telemetry data, handling network edge constraints, intermittent connectivity, and high concurrency.
• Data Lakehouse & ML Pipelines: Hands-on experience designing and operating enterprise data lakehouses using Databricks, Apache Spark, Delta Lake, or Snowflake. Solid knowledge of MLOps pipelines (MLflow, real-time feature stores, model serving frameworks).
• Languages: Technical proficiency in modern language ecosystems used in low-latency/data environments (e.g., Python, Rust, Go, TypeScript).