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AI Workflow Engineer

Alpaca VCNew York, New York🇺🇸United StatesPosted Dec 2, 2025

Why This Role Stands Out

This is a unique opportunity to architect and own end-to-end AI systems that are revolutionizing venture capital, offering significant impact and autonomy in a remote setting. You'll thrive here if you have strong software engineering skills, deep experience with LLM APIs and integrations, and are eager to shape the future of AI in finance. Apply to gain unparalleled exposure to building a cutting-edge AI-first venture capital firm.

Quick Overview

Seniority
Mid Senior
Work mode
Remote
Location
New York, New York, United States
Posted
9 months ago
LLMPython

Job Description

We're building the technical infrastructure for a new kind of venture capital firm—one where AI systems dramatically enhance performance. We need someone who can architect what we’ve scoped out and own these systems end-to-end. 

This isn't about bolting ChatGPT onto existing workflows. We're designing agentic systems that are doing things that took hours across our team. You'll have the autonomy to make architectural decisions and ship production systems that directly impact fund performance. 

You'll work closely with a Principal and General Partner who both understand technical tradeoffs and they’ll empower you with a front-row seat on building a world class venture capital firm in the new era. 

After building our internal systems, you'll deploy this infrastructure across our business units, create technical SOPs, and help us mold our technical platform so that it scales beyond the fund. In other words, this is a high impact and high visibility role designed for someone looking to shape their career in the new AI first economy. 

  • 3-6 years of software engineering or technical product experience, with demonstrated ability to ship production systems 
  • Strong Python or other object oriented programming skills, you've written services that process real data, not just scripts 
  • Deep experience with APIs, webhooks, and integration architecture—you understand auth flows, rate limits, and failure modes 
  • Hands-on experience with LLM APIs (OpenAI, Anthropic, etc.) and prompt engineering for production use cases 
  • Familiarity with workflow orchestration
  • Experience designing data models and working with CRMs and data models  

  • Architectural ownership, you'll make real decisions about how systems are built, not implement someone else's spec 
  • Direct exposure to venture capital deal flow, LP relationships, and portfolio operations 
  • Work with leadership that understands technical tradeoffs and values engineering excellence 
  • Greenfield systems, you're building new infrastructure, not maintaining legacy code 
  • Path to platform business: deploy your systems across portfolio companies as a product 
  • Competitive compensation and the chance to shape the future of work by crafting your role directly 

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