AI Builder & Automation Intern (US)

Location: New York City (Hybrid, ~3 days/week in office)

Type: Full-time internship (≈3 months)

Start: October 2025

Compensation: $50,000 - £60,000 per year (prorated for internship length)

Reports to: Darren Govender, Lead Pricing Actuary

Why this role

We’re looking for someone who enjoys building practical automations that make teams faster. You’ll work with our US Sales & Marketing pod to spot repetitive tasks, design simple automated workflows, get them into production, and measure the impact. Your work will help us decide whether to scale this into a permanent capability.

What you’ll do

• Deliver impact quickly. Ship 2–3 production automations by the end of the internship (e.g., lead enrichment, meeting-notes → CRM updates, follow-up drafting, lightweight reporting).

• Build and integrate. Use platforms like Zapier/Make/n8n and light Python/JavaScript to connect tools (CRM, marketing automation, documents, chat, calendar, data stores) via APIs/webhooks, with sensible error handling and retries.

• Make it visible. Create a simple dashboard (Notion/ or a small web view) that shows runs, success rate, time saved, and common errors. Add basic alerting for failures or missed SLAs.

• Iterate with users. Run two improvement cycles based on usage data and Account Executive feedback. Write short release notes and track adoption and satisfaction.

• Enable and document. Publish short playbooks (how we choose what to automate, security/PII basics, and how to request an automation). Run two internal demos to share what you’ve shipped.

• Work smart with stakeholders. Shadow AEs, map “current vs future” steps, define a small first scope, and ship weekly where possible.

Examples you might tackle

• Auto-enrich inbound leads and post clean updates to the CRM with an audit trail.

• Turn meeting notes into structured CRM fields and next actions, with a light review step.

• Draft prospect follow-ups using recent notes and documents for AE approval.

• Simple reporting nudges (calendar/CRM hygiene; pipeline health summaries).

What you’ll bring

You like to build, ship, and learn quickly. A portfolio, hackathon work, or class projects can be as valuable as formal experience.

Must-haves

• Familiarity with at least one automation platform (Zapier, Make, n8n, Lovable/Replit agents).

• Comfort working with APIs/webhooks/JSON, plus basic Python or JavaScript for glue code and data transforms.

• Sensible judgment about when to use rules vs. AI tools; awareness of speed, cost, and accuracy trade-offs.

• Basic data skills (CSV/JSON handling, SQL) and clear thinking about simple schemas.

• Reliability mindset: logging, retries/backoff, avoiding duplicate runs, and simple Git/PR workflows.

• Clear communication: explain trade-offs to non-technical partners and write concise docs.

Nice-to-haves

• Prior internships/projects in Tech/RevOps or sales-adjacent automation.

• Exposure to modern data stores or vector databases (e.g., Pinecone/Supabase)—not required.

How we’ll define success

By ~3 months you’ve:

• Shipped 2–3 automations to production hitting the targets above.

• Stood up a simple dashboard and alerts, and completed two data-led iterations.

• Published playbooks and delivered two enablement sessions (aim for CSAT ≥4/5).

• Shown hx values in action beyond your core deliverables.

30/60/90 (how we’ll support you)

• 30 days: Shadow AEs, map 5–7 workflows, pick the top 2 by impact/effort; ship POC #1; set up logging + dashboard skeleton; write a short runbook.

• 60 days: Take POC #1 to GA (adoption ≥50%); ship POC #2; add retries/alerts; first enablement; iteration #1.

• 90 days: 2–3 GA automations with target metrics; dashboard live; playbooks published; iteration #2; tidy handover docs.

Why hyperexponential

• Real impact, fast. Small US squad, tight feedback loops, and measurable outcomes “a startup inside a scale-up.”

• Great exposure. a16z-backed, exec visibility, and direct access to the US GTM team.

• Future path. Strong chance of conversion toward RevOps/Enablement (AI-aware) or Automation Engineer. If not, you leave with shipped work, data to show impact, and a strong reference from a fast-growing insurtech.

Interview process

We’re running this process with care and intention. Applications will remain open until Monday 22nd September, and we’ll begin reviewing them together with the hiring team only after the deadline has passed. Please don’t feel the need to rush - take your time to put forward your best application. Every application will be read carefully and considered in detail.

1. Talent screen:

2. Hiring Manager + Skills Interview

3. Values interview:

If this role excites you but you don’t tick every box, please apply, you may be a great fit.

Diversity @ hyperexponential

We’re a high-energy, low-ego, kind team. We believe the more inclusive we are, the better our work and culture. We welcome applicants from all backgrounds and do not discriminate on the basis of race, religion, national origin, gender identity, sexual orientation, age, disability, or veteran status.

Please note that background checks will be conducted as part of the hiring process to ensure compliance with our governance policies. We handle all background checks sensitively and in full compliance with relevant regulations. All applicant data will be processed in accordance with data protection regulations and our privacy policy.