Senior AI Controls Solutions Engineer (Australia)

• Use Phaidra's platform and tools to put AI into production, leading complex, high-impact implementations across multiple data center customers.
• Create models of facilities for ingestion by Phaidra's product lineup, commission and tune products, and provide ongoing support and performance monitoring.
• Work with product team to identify and define product requirements based on customer specifications, translating needs into documentation for software development.
• Act as internal and customer-facing subject matter expert, delivering platinum support, providing technical advice, and supporting sales and marketing.

This role directly enables industrial facilities to reduce energy consumption and improve efficiency through AI-powered control systems, contributing to climate change mitigation by optimizing data center cooling and other industrial processes.

• 10-15 years of work experience as a controls engineer, programmer, or equivalent.
• Expertise in HVAC and Data Center cooling control methodologies, chiller plant fundamentals, and sequence of operations.
• Experience designing, programming, or strong working knowledge of industrial control systems and protocols such as BACnet and Modbus.
• Ability to read and write Python scripts; proficiency in PLC, ladder logic, text, or block programming languages.

Fast-paced, team-oriented environment; 100% remote company; competitive compensation & meaningful equity; outsized responsibilities & professional development; medical, dental, and vision insurance; unlimited paid time off with required minimum of 20 days per year; paid parental leave; flexible stipends for workspace, well-being, and professional development; company MacBook.

Base salary ranges (AUD): Tier 1: $228,627 - $314,362; Tier 2: $205,764 - $282,926; Tier 3: $185,188 - $254,633; Tier 4: $166,669 - $229,170.

Phaidra builds AI-powered control systems for the industrial sector, using reinforcement learning to enable facilities to automatically learn and improve over time, reducing energy consumption and operational inefficiencies.