How to apply for Senior AI Controls Solutions Engineer (Australia/Singapore)

About Phaidra

Phaidra builds AI-powered control systems for industrial facilities like factories, power plants, and buildings. The company applies reinforcement learning to convert raw sensor data into control actions, so facilities can adapt and improve instead of running on hard-coded rules. The team's background includes DeepMind's AlphaGo and reducing Google data center cooling energy by 40%.

About the role

This role involves deploying and configuring Phaidra's AI control agents for industrial customers across Australia and Singapore. You act as the bridge between the customer's domain experts and Phaidra's reinforcement learning systems, helping users define what they want their agents to do without writing code. The work directly affects energy waste and environmental impact at large facilities.

A typical day

A typical day might involve a call with a customer's operations team to review how their AI agents are performing against KPIs, followed by configuring or adjusting agent settings based on that feedback. You might also travel to a site to observe sensor data and control behaviour firsthand, then coordinate with Phaidra's engineering team on any changes needed. Exact routines depend on the customer and region, so ask about travel expectations and on-call responsibilities during interviews.

Who Phaidra is looking for

• Has hands-on experience with industrial control systems (PLCs, SCADA, DCS) and understands how facilities like power plants, factories, or buildings are actually operated.
• Can work directly with domain experts to translate operational goals into configurations for AI agents, without requiring those experts to code.
• Has applied or supported machine learning or reinforcement learning systems in production, not just in research settings.
• Is comfortable working remotely across Australia and Singapore time zones and travelling to customer sites as needed.

Tips for this application

• Name specific industrial control systems you have worked with (e.g., specific PLC brands, SCADA platforms, or DCS vendors) in your resume and cover letter. Phaidra's customers run real facilities, so concrete system experience matters more than general AI knowledge.
• Reference Phaidra's published work on Google data center cooling and AlphaGo in your application. This shows you understand where the team comes from and how they think about applying RL to physical systems.
• Explain how you have worked with non-programmer domain experts to configure or tune a technical system. Phaidra's model depends on users configuring agents without writing code, so this skill is central.
• Address the Australia/Singapore coverage explicitly. State your location, work authorization, and willingness to travel to industrial sites in both regions.
• If you have experience converting raw sensor data into control decisions or KPIs, describe a specific example with measurable results. Avoid vague claims about 'optimizing processes'.

What to cover in your cover letter

Focus on: (1) a specific industrial facility or control system you have worked with and what you did there; (2) your experience configuring or deploying AI/ML systems for non-technical users; (3) how you handle the gap between domain experts' goals and technical implementation; (4) your familiarity with Australia and Singapore industrial markets or your readiness to cover both regions.

Research before applying

• Read Phaidra's published material or case studies on the Google data center cooling project to understand their RL approach in practice.
• Look up the specific industries Phaidra targets (factories, power plants, buildings) and identify which control systems and sensor setups are common in each.
• Check Phaidra's careers page and any public interviews with leadership to understand how the solutions engineering team is structured and what customers they currently serve.
• Research industrial AI control competitors and how they position against hard-coded rule-based systems, so you can speak to tradeoffs in an interview.

Likely interview topics

Based on the job description, expect questions about:

• How you would onboard a new industrial customer's domain experts onto Phaidra's agent configuration system.
• A walkthrough of a control system you have worked with: what data it produced, what decisions it made, and where it failed.
• How reinforcement learning differs from traditional rule-based control, and where each is appropriate.
• How you would handle a customer whose KPIs are not improving after an AI agent is deployed.
• Your approach to working across Australia and Singapore time zones and travelling to remote industrial sites.

Common mistakes to avoid

• Applying with only generic ML or software experience and no industrial controls background. This role requires understanding how physical facilities operate.
• Treating the role as a pure software engineering position. The job is customer-facing and requires working with domain experts who do not code.
• Ignoring the dual-region aspect of the role. If you cannot cover Australia and Singapore or are unclear about your location and travel ability, the application looks incomplete.