InfraBe
Head of Software Engineering - Energy Trading & BESS Optimisation
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Private Equity Backed European Renewable Energy Platform - Battery Storage, Solar & Wind
Location: London/Europe (Flexible)
The Role
To architect, scale, and deliver 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.
Crucially, pioneer 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.
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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).
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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).
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