AI Platform Engineering Intern

Описание вакансии

Antora builds and deploys thermal energy storage to power always-on industrial operations and data centers with low-cost energy. Factory-built in California, Antora’s thermal batteries deliver reliable and cost-effective heat and power for industrial loads of any size. Antora is electrifying global industry while supporting U.S. manufacturing jobs, lowering costs for energy consumers, and enhancing the competitiveness of American industry.

We are growing our company with people who put team and mission first, value connection through laughter and joy, and build with humility and openness. We are committed to continue building a diverse, passionate, and creative team dedicated to a future where every industrial facility, everywhere on earth, is powered by abundant, clean, low-cost energy.

Position Summary

The Platform Engineering Intern at Antora will design and build the AI agent platform that makes our Product Management & Analytics team (PM&A) dramatically more effective. In this role, you will connect frontier AI models to Antora’s proprietary data, domain expertise, and operational workflows — turning generic AI tools into purpose-built agents that accelerate how our team analyzes energy markets, manages assets, and serves customers.

This internship is built around two expected outcomes:

1. Mission-critical project impact: you will design a production AI platform architecture and ship working AI agent plugins that real team members use daily to do their jobs faster and better.
2. Lasting AI adoption: you will build reusable data connectors, encode domain expertise into agent instructions, and stand up governance and evaluation infrastructure that the team scales on long after your internship ends.

The AI tools transforming every industry need the clean power that Antora provides. This is a rare role where you build cutting-edge AI systems and help solve climate change at the same time.

Roles & Responsibilities

• Interview domain experts on the PM&A team to understand workflows, data sources, decision patterns, and automation opportunities, starting with targeted interviews to select the first MVP workflow.
• Capture institutional knowledge as structured Standard Operating Procedures (SOPs) that become the brain of Antora’s AI agents, encoding what matters, why, and how domain experts make decisions.
• Build modular data connectors (MCP servers) to Antora’s proprietary data sources: energy market data, operational telemetry, financial systems, and internal documentation.
• Package 1–2 end-to-end AI agent plugins with domain expertise baked into agent instructions, data access, behavioral guardrails, and human-in-the-loop review workflows.
• Stand up governance and evaluation infrastructure: agent identity and access controls, execution governance, observability tracing, cost attribution, evaluation datasets, and audit trails.
• Generalize learnings from the first two bundles into a written architecture recommendation, a four-layer platform blueprint (data connectors, agent skills, governance & observability, distribution) that the team scales on.
• Validate with real users and iterate based on feedback throughout  not just at the end.
• Document all architecture decisions, tools, and processes so they can be maintained and iterated on after the internship ends.

Key Qualifications

• Builder mentality: you’ve taken projects from idea to working software and prefer shipping real systems over writing papers.
• Systems thinking: ability to design modular architectures that are resilient to change, reason about how components interact, and make sound technical tradeoffs.
• Strong communication: ability to interview domain experts, distill complex workflows into structured documentation, and present architecture recommendations to non-technical stakeholders. Communication is as important as code in this role.
• AI fluency: demonstrated experience building with LLM APIs, AI-assisted workflows, or agent-based systems. You understand where AI adds value versus where human judgment is needed.
• AI experimentation mindset: proactively explores new AI tools and frameworks; thinks critically about architecture decisions in a fast-moving ecosystem.
• Proficient in Python (data pipelines, backend services, APIs, or integration tooling) and comfortable writing SQL for analytical queries.
• Currently pursuing or recently completed a degree in CS, Data Science, Information Systems, or related field. Relevant internship or project experience matters most — we care more about what you’ve built than your degree level.

Additional Qualifications Desired

• Hands-on experience with LLM APIs (Claude, OpenAI, or similar) and prompt engineering.
• Familiarity with MCP (Model Context Protocol), RAG architectures, or vector databases.
• Experience with observability or evaluation tools (Langfuse, Braintrust, OpenTelemetry).
• Background in platform engineering, developer tools, or internal tools.
• User research or requirements gathering experience.
• Exposure to AI governance, identity management, or enterprise security frameworks.
• Graduate degree (Master’s) in CS, Data Science, or related field.
• Prior work on energy, climate, or industrial technologies.

Work Location:  Onsite - San Jose, CA

Internship Start Dates:

Group 1: June 2nd - August 8th

Group 2: June 16th - August 22nd

Hourly Range:  $35 - $45 USD

Please note that the hourly range listed for this position reflects Antora Energy's estimated pay rate. The actual rate offered will be determined based on a candidate's experience, year in school, and degree, as they relate to the position's requirements.

Additionally, this position does not offer visa sponsorship. Only candidates with current work authorization (e.g., F-1 visa with OPT/CPT authorization) will be considered.

#LI-Onsite

!]() [  When it comes to stopping climate change, we need everyone. We believe that having a diversity of backgrounds and experiences strengthens all of us, and we strive to create an environment where every one of us is empowered to create meaningful change.