Principal AI Engineer (Full-Stack) - Stackpoint Ventures

About Stackpoint

Stackpoint is a venture studio that conceives, builds, launches, and scales AI-native companies in high-barrier verticals like real estate, construction, hospitality and financial services. Led by co-founders who have both built unicorn real estate tech companies from scratch, we're a tight team of engineers, product managers, designers, and operators with decades of experience building products, teams, and businesses from startup to scale.

We focus all of our energy on discovering and solving customer and business problems, designing financially strong and defensible business models, activating growth engines, hiring world-class founding teams, and helping them thrive (and none of our energy on big-company b.s.). Our dedicated capital, experienced team, proven process, and deep strategic network supercharge founders and accelerate growth. We're based in Boston but have a distributed team, work remotely and come together every quarter for in-person team building.

We're building a pooled, Studio-wide engineering team — and we're looking for principal-level engineers who want to build across an entire portfolio of companies, not just one.

The Role

Context - How the Studio operates: We launch one new company per quarter. For each, we embed a pod — a dedicated PM, Designer, and one or more Studio Engineers — for ~6 months alongside a founding CEO we recruit and back. The first three months focus on discovery: identifying the wedge product, assessing technical feasibility, and accumulating design partners. The second three months shift to building the wedge while hiring the company's founding technical team (Head of Engineering, sometimes 1-2 IC engineers or contractors) in parallel. Because launches are staggered quarterly, at any given time the Studio is hands-on in ~2 companies at different stages. Shared resources across Marketing, Sales, Finance, Ops, and Recruiting flex across companies during the first 6-12 months based on what's needed to hit key milestones.

As a Principal Engineer, you are the person who builds. You'll typically embed with a single portfolio company for several months at a time — architecting, coding, and shipping backend systems and responsive frontends from prototype through MVP launch. As that company graduates to its own engineering team, you'll roll onto the next build, bringing compounding experience across domains and tech stacks. You'll partner directly with PMs, designers, and founding CEOs to turn discovery insights into functional software.

This is a hands-on, full-stack IC role. You'll report to the Studio's Head of Engineering and you'll be expected to own entire product surfaces end-to-end: cloud infrastructure, APIs, data pipelines, UIs, and deployment — often on the same product. Technology choices are problem-driven, not preference-driven, and you articulate tradeoffs clearly.

AI-native development is core to how you work — both in your engineering workflow and in the products you ship.

What You'll Do

Full-Stack Product Development

Architect, build, and ship AI-native products from prototype through MVP launch — agentic workflows, structured outputs, retrieval patterns, API integrations, and end-to-end systems where LLMs create real customer value. Make grounded model selection decisions and build evaluation methodology for non-deterministic systems. You own the backend, frontend, and AI engineering stack as a unified system.

Infrastructure and DevOps

Set up and manage deployment environments, CI/CD pipelines, logging, and monitoring for new builds using modern cloud or hosted tools. Make pragmatic decisions that prioritize speed and reliability in early-stage systems.

Deep Engagement, Then Rotation

Embed with a portfolio company for the duration of its Studio-led build (typically ~6 months). Own the technical execution alongside the pod. When the company transitions to its own team, roll onto the next build with fresh context and compounding experience.

Product Collaboration

Partner with PMs, designers, and founding CEOs to translate discovery insights into functional software. Contribute to feasibility assessments and help teams understand what's buildable, what's risky, and what's worth a "build to learn" bet.

Technical Transition Support

Help portfolio companies hire their own engineering teams (Head of Engineering, senior ICs) and execute clean handoffs of Studio-built systems within ~6 months of launch.

Studio Tooling and R&D

Contribute to internal tools and reusable frameworks that create compounding leverage across the Studio's portfolio companies.

What We're Looking For

Experience And Background

• 5+ years of software engineering experience with meaningful exposure to modern product/engineering cultures and varied company stages
• Building in early-stage 0→1 environments (seed to Series A), operating in high-ambiguity settings and contributing from concept through launch
• Comfortable with ambiguity, rapid iteration, and the chaos of pre-product-market-fit development

What You Bring (The Essentials)

• Agentic AI: Experience building AI-driven workflows in production (orchestration, tool-use, multi-step reasoning). You know how to make LLM-powered systems reliable in real-world B2B contexts—not just prototypes (evaluation methodology, structured outputs, retrieval patterns, prompt design, and model tradeoffs).
• Data Pipelines: Experience ingesting unstructured or messy data sources (PDFs, documents, web scrapes, APIs) into vector stores (embeddings) and databases (Wide column stores, SQL/NoSQL) for downstream AI queries (semantic search).
• 0→1 Building: You’ve taken products from “blank page” to production launch—not just features within established products. You’ve built and shipped from concept through launch and early iteration in early-stage or startup environments. You architect for the long term, but optimize for rapid learning and execution in the early build phase.
• Full-Stack Ownership: You are proficient in the modern stack (Python/Node + NextJS/React/Vue.js) and can take a build from local development to production deployment using modern cloud or hosted infrastructure.
• Secure Architecture Principles: Understanding of software and AI attack surfaces, secure coding, and handling of PII or sensitive data in regulated industries.

Bonus Points if You Have...

• Experience with Multimodal AI in production systems (image/video/voice understanding and/or generation)
• Prior venture studio experience or product-discovery consulting (where you've worked alongside clients to scope ambiguous problems)

Working Style

• Context-switching is a feature, not a bug. You find variety energizing and ramp fast into new domains, codebases, and team contexts
• Speed and pragmatism define your output. You understand the difference between "build to learn" and "build to scale" and make that call explicitly
• You operate on the frontlines of product work. You’re a strong cross-functional collaborator engaging with customers, PMs, designers, and stakeholders in early discovery cycles (onsites, interviews, feedback loops), and using those signals to shape technical and product decisions—not just execute requirements
• You're user-led in your thinking but bold enough to advocate for technical bets when you see an opportunity
• You use AI coding assistants like Cursor and Claude Code as core workflow tools, and you stay current on the rapidly evolving AI tooling landscape, making pragmatic adoption decisions about what genuinely accelerates your work.
• You're driven by craft and impact, not title or territory. You care about quality but aren't precious — you'll throw away a prototype without flinching if the team learns something important
• You're low-ego, generous with knowledge, and someone other engineers want to work with

Why This Role Is Different

• Breadth over depth: You'll touch more industries, domains, and technical challenges in a year than most engineers see in five. Real estate, insurance, construction, finance — each portfolio company is a new problem space.
• Build, not maintain: Every engagement is a greenfield build. You're always working on the hardest, most interesting phase of a product's life — the 0→1.
• A real team, not a solo act: You'll work alongside a small, high-caliber engineering team — plus PMs, designers, and operators — who are collaborative, low-ego, and deeply experienced at building from scratch. This isn't a lone-wolf contractor gig; it's a tight team that learns and compounds together.
• Leverage over repetition: Your Studio tooling and R&D contributions don't just serve one product — they accelerate every future company Stackpoint creates.
• Direct impact: You'll work directly with founders, the full Stackpoint Studio team, and portfolio company customers. No layers. No politics. Just building.

Logistics

• Compensation: Competitive base, comprehensive health benefits + equity participation in every company we launch during your time here.
• Location: Flexible within U.S. and Canada— we operate remotely.
• Reports to: Studio Head of Engineering.