AI Builder Fellowship: PE Fund + Portfolio

Position Overview

The AI Hive is Tower Brook’s new fellowship for applied AI builders. This is not an analyst program and it is not a consulting role. Fellows do not produce slides about what AI could do. Fellows train intensively inside Tower Brook for six months, with the opportunity to progress into a twelve-month embed inside one of our portfolio companies as an Applied AI Engineer, working directly with CEOs and operating teams to ship AI‑native solutions that move real numbers.

The fellowship runs in two phases. In Phase 1 (six months), fellows are based at Tower Brook in New York or London, training with leading external AI partners and shipping high‑priority internal projects across the firm. Fellows who excel in Phase 1 are considered for Phase 2 (twelve months): a full‑time, onsite embed inside a Tower Brook portfolio company, working in person alongside the management team and reporting to the CEO, CTO, or Head of AI, and delivering milestone‑based work with measured business outcomes.

Fellows in this first cohort will have a unique opportunity to shape how Tower Brook builds and deploys AI talent across the portfolio.

• Complete a three‑week intensive training program with a leading AI‑native training partner, covering prompt engineering, agent architecture, Claude Code and other coding assistants, workflow automation (n8n, Lovable), Python, and enterprise AI governance.
• Pair with internal devs and senior engineers from best‑in‑class applied AI firms on live Tower Brook projects, shipping working prototypes within the first six weeks.
• Lead at least two internal builds with named senior sponsors as business owners. Projects may span front, middle, or back office (investment teams, operations, finance, IR, compliance, knowledge management) depending on firm priority. Deliver shipped output, not recommendations.
• Contribute to the shared Hive knowledge base (reusable agents, templates, playbooks) that compounds across future cohorts.

• Match into a portfolio company across Tower Brook verticals based on fit, and relocate as needed to work onsite at the company’s primary office for the duration of the twelve‑month embed. Matching is jointly led by the Program Lead, the senior program sponsor, and Tower Brook’s Technology Operating Partners.
• Run a four‑week diagnostic sprint: map workflows, validate pain points, and produce a twelve‑month build roadmap signed off by the company CEO and the TCP sponsor.
• Execute three to five milestone‑based build sprints of eight to twelve weeks, each delivering measured output (hours saved, revenue uplift, cost reduction, new capability shipped).
• Report directly to the company CEO, CTO, or Head of AI, while retaining ongoing connectivity to Tower Brook for the duration of the engagement.
• Attend monthly Hive‑wide cross‑pollination sessions with other fellows and coordinators. Document learnings for the Hive knowledge base.
• At the close of the twelve‑month deployment, transition into one of four paths: a full‑time role at the portfolio company, redeployment to a second company, a role at Tower Brook, or release into the TCP alumni network.

• One to three years of post‑university experience in a builder role. We read “builder” broadly: software engineering, data, product, operations with automation exposure, quantitative research, consulting with hands‑on implementation, or early‑stage startups. Candidates with fewer than one year or more than three years of experience are out of scope for the pilot cohort.
• A technical or quantitative undergraduate background is welcome: computer science, engineering, physics, applied mathematics, statistics, computational biology, industrial engineering, operations research, information systems, or quantitative economics. We will also consider non‑technical majors with visible builder evidence such as a Git Hub portfolio, shipped side projects, or published technical writing.
• Fluency with modern AI tools. You already use Claude or ChatGPT daily as a core part of your workflow, not as a…