AI Engineer Internship | Undergraduate or Graduate - Summer 2027
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). Include a section only when posting has real, specific content. Do not repeat job title as heading. Do not put Job ID etc. Remove boilerplate, duplicated lines, application instructions. Preserve all substantive info.
We need to decide which sections to include.
From posting:
- About The Role (section)
- Key Responsibilities (list)
- Skills And Qualifications - Who You Are (list)
- HIRING TIMELINE (maybe not needed? It's metadata but could be considered schedule? Not exactly. It's timeline: applications close, interview process, offer extension. Might be considered schedule? But schedule section is for work schedule. The posting includes Program Duration, Pay, Structure. Those are specific: Program Duration: June 7th, 2027 to August 13th 2027; Pay: New York State minimum wage ($17/hr), up to 40 hours/week; Structure: hybrid internship in NYC, three days per week at HQ.
Thus we can have sections: About the role, Responsibilities, Skills And Qualifications, Program Duration, Pay, Structure. Possibly also About Endeavor (description of company). That is substantive. Could be a section "About Endeavor". The instruction list includes About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. But we can also add other headings if needed? It says use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't forbid other headings, but likely they expect those. However we can include About Endeavor as a section maybe under "About Endeavor". Not in list but could be okay. Safer to stick to given headings. But we have content about Endeavor that is substantive; we could put it under "About the role"? No, that's separate. Could we put under "About the role"? No. Could we create a section "About Endeavor" as a heading? The instruction says use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't say we cannot use other headings, but to be safe we could treat "About Endeavor" as part of "About the role"? Not ideal. Maybe we can include a section "About Endeavor" as a heading; it's still an h3. The examples are not exhaustive. I'd include it.
We must not include filler like "commensurate with experience". Not present.
We need to remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions. The posting includes "HIRING TIMELINE" etc. That's not boilerplate; it's substantive timeline. Should we include? Possibly as a section "Hiring Timeline". Not in examples but could be okay. However they said prefer few substantive sections over many thin ones. Could combine timeline into "Schedule"? Not exactly. Schedule is about work schedule. Timeline is about application process. Might be considered metadata; they said do NOT put Job ID/requisition numbers as headings — fold minor metadata into a short
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't say we cannot use other headings, but to be safe we could treat "About Endeavor" as part of "About the role"? Not ideal. Maybe we can include a section "About Endeavor" as a heading; it's still an h3. The examples are not exhaustive. I'd include it. We must not include filler like "commensurate with experience". Not present. We need to remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions. The posting includes "HIRING TIMELINE" etc. That's not boilerplate; it's substantive timeline. Should we include? Possibly as a section "Hiring Timeline". Not in examples but could be okay. However they said prefer few substantive sections over many thin ones. Could combine timeline into "Schedule"? Not exactly. Schedule is about work schedule. Timeline is about application process. Might be considered metadata; they said do NOT put Job ID/requisition numbers as headings — fold minor metadata into a short
or drop it. Timeline might be considered minor metadata? It's about dates; could be folded into a short paragraph under maybe "About the role" or separate? I'd keep it as a short paragraph under a heading "Hiring Timeline"? Might be considered minor metadata; but they said fold minor metadata into a short
or drop it. So we could include a short p with timeline info under maybe "About the role" or at end. But we have many sections already; maybe better to drop timeline to keep few sections. However the timeline includes important dates: Applications close Oct 7 2026, interview process, offer extension Nov 16 2026. That's substantive for applicant. But they said prefer few substantive sections over many thin ones. Could we incorporate into a "Program Duration" section? No. Could we add a "Timeline" section? Might be okay. But we also have "Internship Program Overview" which describes program details: 10 weeks, location, etc. That's substantive and overlaps with Program Duration, Pay, Structure. Could combine. Thus we can have sections: - About the role - Responsibilities - Skills and Qualifications - Program Details (covering duration, pay, structure) - About Endeavor We need to use
for each heading. Inside each section, use
for prose,
- for lists.
We must preserve all substantive information. Let's extract.
About The Role paragraph: multiple sentences. We'll keep as
. Key Responsibilities: list of 5 responsibilities each starting with "Responsibility #X:". We'll make
- each. Skills And Qualifications - Who You Are: includes bullet points with headings? Actually it's a paragraph then bullet list with headings: Student Status, Interests/Areas of Focus, etc. We'll treat each bullet as
- with its content. We need to capture all bullet content: - Student Status: Undergraduate Junior or Senior, or Graduate student in Computer Science, Data Science, Information Systems, Business, or a related field; candidates from other disciplines with relevant skills and demonstrated building experience are encouraged to apply. - Interests / Areas of Focus: Strong interest in applied AI and how organizations, not just individuals, adopt it: workflows, governance, change management, and knowledge systems. Hands-on experience building with LLMs beyond casual chatting: class projects, hackathons, or personal projects involving prompting, agents, RAG, or API integrations (Anthropic/Claude, OpenAI, or similar). Fluency with AI-assisted development tools (e.g., Claude Code, Cursor) is a strong plus. Things you have shipped matter more than credentials. Working knowledge of Python or TypeScript/JavaScript and basic SQL, enough to build a prototype and query data with AI assistance. Ability to understand technical architectures (APIs, databases, retrieval systems) and explain them clearly to non-technical colleagues; much of this role is translating between technical and non-technical worlds. Exceptional written and verbal communication with an analytical-first mindset; comfortable asking "why" to get to the root of a problem and turning research into actionable recommendations. Comfortable working in a multilingual, global, cross-cultural environment and incorporating feedback from multiple stakeholders. Nice to have: familiarity with Git, Snowflake, Salesforce, Notion, or workflow automation tools; interest in entrepreneurship or the startup ecosystem. Must be legally eligible to work in the U.S. We will not be able to interview or select candidates without valid U.S. work authorization for the 2027 year. We'll keep as one
- maybe with line breaks? Could split into multiple
- for readability but it's okay.
Program Duration, Pay, Structure: we can combine into a section "Program Details". Provide
with sentences. Program Duration: June 7th, 2027 to August 13th 2027. Pay: New York State minimum wage ($17/hr), up to 40 hours/week. Structure: This is a hybrid internship in New York City, with three days per week to be spent at Endeavor Global’s HQ office in Downtown Manhattan. Also Internship Program Overview: gives more detail: 10 weeks, side by side with HQ teams in NYC, SF, London, Dubai, Singapore, owning meaningful projects, contribute real work, present to CEO, fireside chats, etc. We'll include that as part of program details. About Endeavor: paragraph describing WHO WE ARE, OUR MISSION, OUR MODEL, etc. We'll keep as
. Now ensure we don't repeat job title as heading. Not needed. We must not include boilerplate like "Read more about out program here" (typo). That's a link; we should remove. Also "Read more about out program here About Endeavor" appears; we should drop that line. Also "Read more about out program here" is likely a link; we drop. Also "Read more about out program here About Endeavor WHO WE ARE:" Actually the text: "Read more about out program here About Endeavor WHO WE ARE:". We'll drop the "Read more about out program here" phrase. Now produce HTML fragment. Let's craft.
About the role
Endeavor's Platform team builds the data, tools, and AI infrastructure that powers our global network across 50+ markets. With Claude Enterprise now deployed to 390+ staff across 43+ markets, access to AI is no longer our constraint. The next challenge is organizational: converting that access into institutional capabilities that one team can build, another market can reuse, and Endeavor retains when people move on. We're looking for a curious, hands-on, builder-minded intern to help create Endeavor's AI organizational infrastructure: the reusable capabilities, templates, governance rails, and enablement systems that let our local offices and functional teams design their own AI-augmented processes safely and effectively, instead of 50 markets reinventing the same tools in isolation. This is not a shadowing role. It is a hybrid role between discovery and applied AI engineering. You will interview local offices and functional departments to understand their workflows and what infrastructure they actually need, and you will get your hands dirty: prototyping agentic workflows, Claude skills, MicroApps, and retrieval systems on Endeavor's enterprise AI stack (Claude Enterprise, MCP integrations, Snowflake, Salesforce, and Notion). You will also support the Platform team's deeper work on knowledge capture and institutional memory, helping turn the network's interactions into structured, trusted, actionable knowledge. By the end of the internship, you'll have shipped real capabilities used by teams across markets, creating a tangible output with lasting impact on how nearly 500 Endeavor colleagues work worldwide. This internship is ideal for someone excited by applied AI, organizational systems, and building things that scale globally, while gaining real responsibility and visibility inside a mission-driven organization.
Responsibilities
- Responsibility #1: Discover What Teams Actually Need – Lead structured interviews with local offices and functional departments to map their workflows, pain points, and existing AI experiments. Find where a shared, governed capability would beat fifty isolated ones, and identify what infrastructure, training, or guardrails each team needs to build effectively on their own.
- Responsibility #2: Build Reusable AI Capabilities – Prototype agentic workflows, Claude skills, MicroApps, and retrieval features on our enterprise stack (Claude Enterprise, MCP, APIs), always choosing the lightest technical pattern that supports the behavior we want. Package what works so another market can adopt it without rebuilding it.
- Responsibility #3: Create the Enablement Infrastructure – Help create the templates, playbooks, starter kits, and documentation that let teams self-serve: how to build a skill, an Artifact, a plugin, etc.; how to connect to governed data and use our MCPs; and how to stay within Endeavor's AI Policy. Make the right way the easy way.
- Responsibility #4: Support Knowledge Capture & Institutional Memory – Support the Platform team's work on turning captured knowledge (meetings, founder ratings, network interactions) into structured, actionable intelligence, including retrieval pipelines and early knowledge graph work that makes institutional memory usable at the moment of key decisions.
- Responsibility #5: Govern and Evaluate What You Ship – Define what "working" means for the capabilities you build: success metrics, output quality checks, and simple eval loops. Contribute everything to Endeavor's AI Registry so it is human-owned, tracked