via Workable
$120K - 160K a year
Architect and own end-to-end AI-enhanced technical infrastructure for a venture capital firm, deploying systems across business units and shaping scalable technical platforms.
3-6 years software engineering with production system shipping, strong Python and LLM API experience, deep API and integration knowledge, workflow orchestration familiarity, architectural ownership, and venture capital exposure.
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
This job posting was last updated on 12/4/2025