Technical Product Systems Intern (AI & PLM)

This is a 10-week internship starting June 8 or 15 and is fully on-site at the listed office location.

Company Overview

At Bloom Energy, our vision for a world powered by clean, reliable, and affordable energy is more than just a dream—we’re making it a reality.

 
For over two decades, we’ve been at the forefront of the global energy transition, pioneering solutions that empower critical industries to thrive in a rapidly digitizing, energy-intensive world. From revolutionizing power for AI-driven data centers to ensuring resilience for hospitals, electric grids, manufacturing facilities, and utilities, our solid oxide fuel cell (SOFC) and solid oxide electrolyzer (SOEC) technologies are redefining what’s possible by delivering energy abundance for all. With more than 30,000 fuel cell modules deployed worldwide, we are the trusted partner for Fortune 100 companies and innovators alike. Our cutting-edge solutions enable unparalleled “time-to-power” capabilities, reliability, and sustainability, ensuring our customers remain ahead in a world where soaring energy demand and intensifying energy scarcity are rapidly becoming the new norm.

 
At Bloom, we thrive on collaboration, bold thinking, and relentless innovation. We believe that, together, we can create a brighter, more sustainable future while tackling the most pressing challenges of the 21st century.

Department Overview

The Product Group reports to the CTO office and is responsible for all product-related technical documentation and training. The Product team owns Bloom’s Project Configurator and is responsible for keeping it up to date with the latest product and solution offerings. This team serves as a bridge between engineering and commercial teams, providing the right collateral, information, value propositions, and tools to secure new business.  

Position Responsibilities

This intern will aid in the design and development of an AI‑enabled system that connects directly to Bloom Energy’s Product Lifecycle Management (PLM) platform to identify, retrieve, and validate the correct, released technical documents based on keywords, product context, and semantic similarity. The goal is to improve document accuracy, revision correctness, and confidence in downstream product, sales, and engineering workflows. This is a high-visibility project that requires the intern to work cross-functionally with multiple groups (e.g., IT, engineering, and product teams) to ensure the tool is developed and validated with stakeholder buy-in.

Required Skillsets

This project is anticipated to extensively use artificial intelligence to enable intelligent document search, classification, and validation within a PLM‑managed environment. The intern should have demonstrated execution experience in:

• Designing a keyword‑ and semantics‑driven document retrieval workflow that queries PLMs for:
  • Released technical documents
  • Correct revisions and lifecycle states
  • Product / part / model number associations
  • Implement logic to map user queries (keywords, product attributes, use cases) to the correct PLM‑managed documents
• Evaluating and flag document mismatches, outdated revisions, or missing “source of truth” artifacts
• Partnering with various stakeholders to validate PLM data access patterns and APIs

Minimum Qualifications

• Currently pursuing a Bachelor’s, or Master’s degree in Computer Science, Data Science, Software Engineering, Information Systems, or a related technical discipline

• Must be graduating between Spring 2026 and Summer 2027

Desired Qualifications

• MBA candidate with computational background
• Demonstrated proficiency in Python and/or Java, including building data‑driven or API‑based applications
• Experience working with APIs and structured data formats (JSON, REST endpoints)
• Working knowledge of Natural Language Processing (NLP) concepts such as text parsing, similarity scoring, or document classification
• Ability to read, understand, and reason about technical or engineering documentation
• Familiarity with basic enterprise data concepts (documents, metadata, versions, revisions, lifecycle states)
• Strong analytical skills and attention to detail, particularly when validating the correctness of information
• Ability to collaborate cross‑functionally with product, engineering, and IT stakeholders
• Direct exposure to Product Lifecycle Management (PLM) systems, including documents, revisions, lifecycle states, or change objects
• Experience querying enterprise systems via APIs to retrieve structured records and associated documents
• Hands‑on experience with LLMs or AI search platforms
• Defining “source of truth” f