AI Data Engineering Intern - Platform & Agents

Antora Energy • San Jose, CA

13h • Onsite

About The Position

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:
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.
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.
This internship will be on-site in Sunnyvale, CA.

Requirements

• 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.
• Able to work full-time, 40 hours per week, on-site in Sunnyvale, CA.

Nice To Haves

• 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.

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.

Benefits

• equity compensation in the form of stock options
• a premium health benefits package with life and disability insurance
• a 401K plan with employer contributions
• flexible spending accounts
• an industry leading paid-time-off policy that features flexible and inclusive holiday observance
• paid volunteer time off

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Number of Employees: 101-250 employees