
Private Equity Engagement Lead
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Nice to have's
Job description
About the Position
Private Equity Engagement Lead
San Francisco Bay Area
About Brain Co.
Rebuild how the world works, to make institutions work better for the people they serve.
Brain Co. builds AI-native operating systems for large, regulated institutions. Each system is built for a specific industry, powered by agents that push real workflows forward. Underneath it all is Atlas, our proprietary platform that keeps customers in control, secure by design, and never locked into one model.
We were co-founded by Jared Kushner and Elad Gil and are backed by leading Silicon Valley builders including Patrick Collison and Andrej Karpathy. We have raised a $55M Series A and built a team of 70+ from Palantir, Google DeepMind, Meta, NVIDIA, Tesla, and Databricks. Every project here ships to production and is expected to create measurable value:
- Automated construction permitting for a sovereign government → 80% faster, $375M+ in value unlocked
- Optimized supply chains for a leading global energy company → 30% lower cost, 99% reliability, $100M+ in losses prevented
- Streamlined patient care across national health systems → 40% better outcomes, 80% less admin work
We are looking for leaders who want to help bring new technology into institutions that impact millions of people.
Responsibilities
- Run AI diligences end to end. Scope with the deal team, map the target's workflows and data, identify and size the highest-value AI solutions, assess implementation dependencies and competitive risk, and deliver the readout to the deal team and IC.
- Own sponsor relationships. Manage day-to-day communication with deal teams and portfolio executives, and become a trusted voice on AI for the funds you serve.
- Bridge technology and capital. Work with Brain Co. engineers and product leaders to pressure-test feasibility - sometimes by prototyping on the target's own data mid-diligence - and turn the answer into recommendations an IC can underwrite.
- Carry the thesis past the deal. When sponsors bring us in post-close, convert diligence findings into value creation plans, scope solutions with our product and engineering teams, and stay close as they ship.
- Build the practice. Codify diligence frameworks, sector playbooks, and solution patterns that make each engagement faster and sharper than the last.
Requirements
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Experience
- 3–5+ years of professional experience, with a background in top-tier consulting (McKinsey, Bain, BCG), private equity, and/or AI technology companies.
- Experience contributing to complex diligence, strategic analysis, or technical evaluation processes.
- Startup or high-growth operating experience preferred; comfort with ambiguity and moving fast.
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Skills & Attributes
- AI-native. Strong technical literacy in AI/ML: you can hold your own with engineers on models, evals, data pipelines, and architecture trade-offs, and you have a point of view on where AI creates durable value. You do not need to build, but you need to be credible to the people who do.
- PE-native. Commercial instinct and an ownership mindset. You think in EBITDA, multiples, and hold periods, and you connect every AI opportunity back to the deal thesis.
- Executive communication. Proven ability to influence senior sponsors, investors, and portfolio executives, including when the message is hard.
- Exceptional problem-solving and analytical skills; you turn complex analyses into clear insights under time pressure.
- Low-ego, hands-on operator who thrives in ambiguous, fast-paced environments.
- Based in SF or willing to relocate.
Why Join Us
- See the whole market. Dozens of companies a year across sectors, building pattern recognition in AI strategy that is impossible to get in a single-company role.
- Follow your work into production. Unlike a pure diligence shop, Brain Co. builds what it recommends. You will find out whether your thesis held.
- Work at the top of the industry. Direct exposure to deal teams and portfolio executives at the most prestigious PE firms, and to investment decision-making at the highest level.
- Own a scarce skill set. Deep expertise at the intersection of AI and private equity - a niche with rapidly growing demand and very few experienced players.
- Join at the inflection point. Brain Co. has already done the hard part: proving frontier AI can run inside the world’s largest organizations. Now we're scaling those deployments and defining a category that didn't exist two years ago. You'd be joining early enough to shape what the company becomes, and late enough to know it works.
- Competitive compensation and meaningful equity, on a small, high-impact team where your work directly shapes investment outcomes and AI strategy for major portfolio companies.
If you want to sit at the frontier of AI and private equity - working with the most prolific investors in the world and learning at an unparalleled rate - Brain Co. is the place to build.
© Label Your Data. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.
Label Your Data provides secure and high quality data annotation services for Computer Vision or NLP applications since 2020. We help Data Scientists and AI Engineers streamline the dataset labeling and focus on model development.About Label Your Data:— Founded in 2020;— 200+ annotation experts in Europe, LATAM and Africa;— 98%+ annotation accuracy benchmark;— 55 supported languages;— PCI/DSS certified;— ISO/IEC 27001:2013 certified;— GDPR, CCPA and HIPAA-compliant;— HQs in North America, EU and Asia.Our experience spans over 20 industries including Automotive, Robotics, Agriculture, E-commerce, Retail, Healthcare, Manufacturing, Fintech and Insurance.Our core services include but are not limited to:— Image & video annotation: 2D boxes, OCR, object/action detection, polygons, key points, semantic segmentation, 3D cuboids;— Text annotation: classification, NER, intent & sentiment analysis, prompts creation, Q&A pairs generation;— Audio annotation: transcription, sentiment recognition;— Sensor data annotation;— Data classification & categorization;— Data entry;— Data collection;— Model validation.
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