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AI Product Spec Writer

Оценка ИИ

Престижная компания в сфере венчурного капитала с огромными активами. Роль предлагает высокую степень влияния на стратегию компании, работу с передовым стеком (Claude, GPT, Gemini) и привлекательный пакет компенсации, включая опционы.


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Оценка ИИ

Роль требует редкого сочетания навыков: глубокого понимания работы LLM, опыта в системном анализе бизнес-процессов и способности обучать других. Высокая планка ожиданий обусловлена необходимостью работать напрямую с руководством (CTO/CEO) и спецификой венчурной индустрии.

Анализ зарплаты

Медиана175 000 $
Рынок145 000 $ – 210 000 $
Оценка ИИ

Предлагаемая позиция соответствует уровню Senior Product Manager / AI Architect. В регионе Манчестер/Бостон рыночные зарплаты для таких ролей в финтехе и венчуре начинаются от $150k, а с учетом бонусов и опционов совокупный доход может значительно превышать средние показатели по рынку.

Сопроводительное письмо

I am writing to express my strong interest in the AI Product Spec Writer position at Alumni Ventures. With a deep background in technical product management and a specialized focus on AI-native workflows, I am excited by the opportunity to serve as the 'front door' for your technology projects. My experience in mapping complex business processes and translating them into rigorous, shippable specifications aligns perfectly with your need for a senior operator who can bridge the gap between business owners and engineering teams.

Throughout my career, I have developed a keen judgment for where LLMs can provide transformative value versus where traditional software rules are more effective. I am particularly drawn to AV's in-office culture and the emphasis on mentorship and shared momentum. I am confident that my skills in workflow extraction, combined with my ability to design evaluation plans for AI systems, will significantly raise the bar for product development within your organization.

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Присоединяйтесь к лидеру венчурных инвестиций и определяйте будущее AI-продуктов в Alumni Ventures!

Описание вакансии

About Alumni Ventures

Alumni Ventures is one of the world’s most active venture capital platforms, with $1.4B+ in assets raised and investments in 1,600+ companies. Our network of 850,000+ members and 40+ dedicated investors connects accredited individuals to high-quality venture deals—typically reserved for institutions—through our alumni-driven communities and diversified co-investment strategy. With offices in Boston, New York, Chicago, Menlo Park, Manchester, NH, London and Tokyo we’re rapidly growing and committed to fueling entrepreneurial success while developing the next generation of VC professionals.

We believe our best work happens when we’re together. AV operates as a 5-day-a-week, in-office culture because collaboration, mentorship, and shared momentum matter.

About the Role

Alumni Ventures is hiring an AI Product Spec Leader, a senior, AI-native operator to be the front door for tech projects. You will interview business owners, map workflows, identify where AI can materially improve outcomes, and produce shippable specifications that our Tech Team executes. You will also train teammates on workflow discovery and spec-writing skills, raising the bar across AV.

What You’ll Do

Discovery & Workflow Extraction

  • Lead structured interviews with process owners across AV (Ops, Finance, Marketing, Investing, IR).
  • Convert tribal knowledge into current-state workflow maps (swim lanes), bottlenecks, edge cases, and decision points.
  • Clarify goals, non-goals, constraints, data sources, permissions, and handoffs.

AI-first Solution Shaping

  • Identify where LLMs help (summarization, extraction, classification, routing, retrieval, agentic steps) and where rules/software are better.
  • Define human-in-the-loop steps, escalation paths, guardrails, and fallback behavior.
  • Account for security, privacy, and audibility needs from the start.

Write Specs Engineering Can Ship

  • Produce PRDs, user stories, acceptance criteria, data/integration requirements, and launch plans.
  • Specify integrations and data needs across Claude, ChatGPT, Gemini; HubSpot; NetSuite; custom software; and Vertica.
  • Ensure each AI feature includes an evaluation plan and monitoring approach.

Run the Intake + Prioritization Front Door

  • Own the intake pipeline for Tech Team work, ensuring each request is well-defined and sized to ship.
  • Prepare prioritization materials and facilitate decision-making with CTO and CEO.
  • Track progress, risks, dependencies, and weekly KPIs.

Train Others

  • Create and run a lightweight enablement program (templates, short workshops, coaching).
  • Teach interviewing, workflow mapping, spec structure, and AI evaluation basics.
  • Raise spec quality across Tech and business teams through review rituals and feedback.

Who You Are

  • Senior individual contributor experience producing shippable specs for cross-functional software projects (high ambiguity, real stakeholders).
  • AI-native product judgment: understands LLM failure modes and how to constrain and evaluate AI systems.
  • Excellent interviewing and facilitation skills; able to surface constraints and edge cases quickly and tactfully.
  • Strong writing: concise, structured, decision-oriented specs that engineers can implement with minimal back-and-forth.
  • Comfort with integrations and data flows (HubSpot, NetSuite, custom systems, databases such as Vertica).
  • High ownership and pace; thrives in an in-office, startup mentality culture.
  • Experience with workflow mapping methods (swim lanes, BPMN) and process redesign.
  • Experience building scoring/routing systems, RevOps tools, finance ops workflows, or ad ops workflows.
  • Familiarity with evaluation/monitoring patterns for LLM systems.

Our Culture & How We Work at AVRegardless of title, this is what great looks like at AV.

  • Put team and stakeholders first. We win together and measure success by the value we create for our investors, founders, and each other.
  • Take extreme ownership and bias toward action. We act like owners, move with urgency, and follow through.
  • Debate rigorously and commit fully. We welcome diverse views, use data and sound judgment, and once aligned, execute as one team.
  • Focus on what matters most. We prioritize impact, simplify where possible, and channel energy where we have a real advantage.
  • Be AI-forward and tech-optimistic. We actively use AI and emerging technologies to work smarter, make better decisions, and amplify human judgment — not replace it.
  • Stay curious and think big.We are continuous learners, aim high and build for long-term impact.

Benefits & PerksWe offer a flexible, employee-first benefits program designed to support your health, financial well-being, and life outside of work. Benefits begin shortly after hire and are designed to give you choice and flexibility based on your needs.

  • Comprehensive health coverage with multiple plan options, including employer-funded deductible support and HSA contributions
  • Dental and vision plans with multiple coverage tiers
  • Tax-advantaged accounts including HSA, FSA, and commuter benefits (with monthly employer contribution)
  • 401(k) with company match and immediate vesting
  • Company-paid life and disability insurance, plus optional supplemental coverage
  • Additional support programs including EAP, health advocacy, and wellness resources
  • Flexible, unlimited PTO and generous paid parental leave
  • 11 company holidays

Compensation includes base salary plus equity and corporate bonus.

Privacy Policy

All employment is subject to passing a background check. Alumni Ventures is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability status.Privacy Policy

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Навыки

  • LLM
  • Product Requirements Document
  • Workflow Mapping
  • BPMN
  • HubSpot
  • NetSuite
  • Vertica
  • Claude
  • ChatGPT
  • Gemini
  • User Stories
  • AI Evaluation

Возможные вопросы на собеседовании

Проверка способности отличать хайп от реальной пользы AI для бизнеса.

Опишите случай, когда вы решили НЕ использовать LLM в проекте, несмотря на запрос бизнеса. Почему традиционное ПО было лучше?

Оценка навыков системного анализа и работы с 'tribal knowledge'.

Как вы подходите к интервьюированию стейкхолдеров, которые не могут четко сформулировать свои рабочие процессы?

Проверка технической экспертизы в области надежности AI.

Какие метрики и методы оценки (evaluation) вы закладываете в спецификации для систем на базе агентов или RAG?

Оценка лидерских качеств и способности к обучению команды.

Как бы вы построили программу обучения для нетехнических сотрудников, чтобы они начали писать качественные запросы на разработку AI-инструментов?

Проверка опыта работы со сложными интеграциями.

Расскажите о вашем опыте проектирования потоков данных между CRM (например, HubSpot) и кастомными AI-решениями. С какими сложностями вы сталкивались?

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