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Principal Engineer - Stackpoint Ventures in Boston

Job in Springfield, Hampden County, Massachusetts, 01101, USA
Listing for: Energy Jobline ZR
Full Time position
Listed on 2026-05-30
Job specializations:
  • Engineering
    AI Engineer, Software Engineer, Systems Engineer
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

Job Description Job Description About Stackpoint

Stackpoint is a venture studio that conceives, builds, launches, and scales AI-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- development is core to how you work. You use tools like Cursor and Claude Code daily, you've integrated LLMs into production systems, and you have hands-on experience with prompt engineering, structured outputs, and cost/performance tradeoffs. You follow the AI landscape actively and make pragmatic adoption decisions.

What You'll Do Full-Stack Product Development

Architect, build, and ship backend systems and responsive frontends for new products across our portfolio, from prototype through MVP launch.

Infrastructure and Dev Ops

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.

AI
- Development

Leverage AI coding assistants as core workflow tools to accelerate building, iteration, and experimentation. Integrate LLM-powered features into customer-facing systems where they create real value — including agentic workflows, structured outputs, retrieval patterns, API integration, and evaluation of model tradeoffs.

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.…

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