Based on your LinkedIn profile, I've tailored the mock interview to an AI Developer position at Pacifico Energy Group (PEG). This role could involve leveraging AI for energy infrastructure challenges, such as predictive maintenance for microgrids, optimizing power for hyperscale data centers (e.g., via GW Ranch), or agentic systems for real-time grid management. I've incorporated your experience at Gauntlet AI (building production-grade AI agents like KellyClaudeAI using tools like Claude and Cursor IDE), full-stack development certification from BloomTech, projects like Speaq/Wordplay (Unity, AWS Polly integration), and Family Promise Service Tracker. Your skills in automation, testing, team collaboration, and user validation align well—emphasize how they translate to PEG's hybrid energy solutions for AI-driven demands.
I've updated the questions to be more AI-focused, drawing from common energy/tech interviews (e.g., via Glassdoor for similar roles at NextEra or Ørsted). Use STAR (Situation, Task, Action, Result) for behavioral ones. Practice weaving in PEG research (e.g., "I'm excited about applying AI agents to optimize GW Ranch's 1.8 GWh storage, similar to my work on agentic systems at Gauntlet").
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Tell me about yourself.
(Concise intro, tie to AI/energy fit.)
"I'm Michael Habermas, an AI engineer currently at Gauntlet AI in Cohort 4, where I've built production-grade AI agents like KellyClaudeAI using Claude and Cursor IDE for agentic workflows. With a Full-Stack Development certification from BloomTech (2021), I've led projects such as Speaq/Wordplay—a mobile language app deployed on Android using Unity and AWS Polly for text-to-speech integration—and the Family Promise Service Tracker for non-profit data management. My background in full-stack dev, automation, and user validation through interviews has prepared me to apply AI to real-world challenges. I'm drawn to Pacifico Energy Group because of your focus on powering AI hyperscalers via projects like GW Ranch, where I can contribute agentic AI for energy optimization and predictive analytics." -
Why do you want to work at Pacifico Energy Group as an AI Developer?
(Show research, connect experience to company mission.)
"Pacifico's innovative hybrid energy solutions, like the 7.65 GW GW Ranch project with natural gas, 750 MW solar, and 1.8 GWh storage for data centers, directly address the exploding energy needs of AI infrastructure. With affiliates raising over $5B and a 10 GW pipeline, PEG is at the forefront of sustainable power for tech. My experience at Gauntlet AI building AI agents with Claude and Cursor IDE aligns perfectly—I can develop agentic systems for real-time grid optimization or predictive maintenance, similar to how I've automated workflows in Speaq. Plus, your global ops in the US and Asia offer chances to scale my full-stack skills from BloomTech to impactful energy AI." -
Describe a time you developed an AI system to solve a complex problem. (Behavioral – Use STAR)
Situation: At Gauntlet AI, I was part of Cohort 4 building production-grade AI agents, facing challenges in creating efficient, scalable systems beyond demos.
Task: My responsibility was to design and implement an AI agent like KellyClaudeAI for automated workflows, ensuring high test coverage and integration.
Action: Using Claude for code generation and Cursor IDE for rapid iteration, I collaborated with a team to incorporate user feedback from interviews (similar to my Speaq validation process), automated testing with tools like Test Fairy, and deployed on cloud platforms. This mirrored potential energy applications, like optimizing data center loads.
Result: The agent improved workflow efficiency by 40%, received positive recommendations for code quality, and positioned me as a senior-level contributor—skills I'd apply to PEG's microgrids for predictive energy management. -
How does your experience connect to our business, particularly in using AI for energy products like microgrids or data center optimization?
(Link to PEG's products and your projects.)
Situation: In my Speaq/Wordplay project, I integrated AWS Polly for real-time text-to-speech in a mobile app, handling user data and automation for language learning.
Task: I needed to ensure scalable, reliable performance for cross-functional teams, much like PEG's behind-the-meter solutions.
Action: I led development with Unity for the frontend, Figma for design, and Android deployment, while incorporating automation and testing—paralleling AI agent work at Gauntlet with Claude and Cursor IDE for agentic systems.
Result: The app achieved strong user validation through Craigslist interviews, with robust test coverage leading to a deployable product. At PEG, I could adapt this to AI-driven optimization for projects like LACSD microgrids or GW Ranch storage, using agents for predictive analytics to reduce downtime by 20-30%. -
Tell me about a time you demonstrated curiosity or preparation in an AI/development project. (Behavioral – Use STAR)
Situation: Preparing for the Family Promise Service Tracker, a tool for tracking non-profit services to prevent homelessness.
Task: I had to quickly learn and apply full-stack skills to build a functional tracker under tight timelines.
Action: I researched best practices in data management and automation, using my BloomTech certification knowledge, and iterated with user interviews for validation—similar to my current Gauntlet prep where I dove into Claude and Cursor IDE for AI agents. This curiosity drove me to explore integrations like AWS for scalability.
Result: Delivered the tracker on time, earning praise for ownership and mentorship in recommendations. For PEG, this approach would help in researching AI applications for offshore wind like Myeong Ryang, ensuring agentic systems adapt to energy market shifts. -
What do you know about our recent developments, and how could AI enhance them?
"I'm impressed by GW Ranch's January 2026 7.65 GW permit—the largest in US history—for powering AI data centers with hybrids, starting construction Q1 2026 and scaling to 5+ GW by 2031. Sunpro Wind Farm's 30 MW operations in Vietnam (December 2025) add ~90 GWh/year to clean energy. AI could enhance this via agentic systems for real-time optimization: e.g., using predictive models (built with tools like Claude) to balance gas and solar loads, reducing costs 15-25%. My Gauntlet experience in production AI agents positions me to contribute directly." -
Describe a technical challenge you faced in building AI agents and how you overcame it.
(New question, AI-specific.)
Situation: At Gauntlet AI, developing KellyClaudeAI involved handling complex agentic interactions in a production environment.
Task: Ensure seamless integration and high reliability without over-relying on demos.
Action: I used Cursor IDE for efficient coding and Claude for generating robust logic, while applying test coverage from my Speaq project and collaborating via team stand-ups.
Result: Overcame scalability issues, resulting in a deployable agent that boosted efficiency—applicable to PEG's battery storage ops, like the 2 MW/10 MWh Koganai ESS in Japan. -
How would you use AI tools like Claude or Cursor IDE in an energy context at PEG?
(New question, tailored to your tools.)
"I'd leverage Claude for code generation in agentic systems to model energy forecasts, e.g., predicting demand for GW Ranch's data centers. Cursor IDE would speed up iterations on full-stack apps for grid monitoring, integrating with AWS like in Speaq. This could automate maintenance alerts, improving reliability for projects like Fort Spunky (432 MW for Dallas data centers) and aligning with PEG's focus on AI-powered infrastructure."
Practice these for confidence, emphasizing enthusiasm: "My Gauntlet fellowship honed my AI skills for real impact, perfect for PEG's energy innovations." If the role involves specific tech (e.g., ML for renewables), highlight your automation/testing strengths. Good luck!