Applied AI Engineer (Application Deadline: July 16th)

About HqO


HqO is connecting real estate to the people with an asset agnostic, cross-property suite of powerful applications and services that foster best-in-class, dynamic end-user experiences. HqO’s REX (Real Estate Experience) Platform assesses the health and performance of a person’s experience within a physical space while providing the necessary tools for operators to manage and optimize it, all from one central location. 


HqO has been trusted to power 400 million+ square feet across 700+ properties in 32 countries, and we’re backed by some of the world’s most prominent VC and real estate companies as we continue to grow rapidly across the world. 


We’re driven by our core values of LET’S GO (Learning, Excellence, Truth, Service, Goodness, Ownership) which define our culture and push us to do our best work every day. If you want to join a fast-growing, highly collaborative, and supportive team that is at the forefront of real estate transformation, we’re the company for you.

Please see the bottom of this application for more details on how to apply!

About the Role

HqO is leading the transformation of the way people experience real estate by converging data, technology, and the customer. Empowering data-driven strategies and real estate decisions, we're redefining the way people experience space, and in turn, helping to create vibrant, engaging communities.Our REX Platform is used by leading commercial real estate owners and occupiers to activate their spaces, engage tenants, and measure what matters. We are a 100-person company that moves fast, operates with high ownership, and takes AI seriously and a culture that rewards builders.


We're hiring our first Applied AI Engineer: someone who will embed directly with our Operations and DevOps teams to identify high-leverage problems, build production-grade AI agents and automations, and ship tools that make the company measurably more effective.


We care less about where you trained and more about what you've built. We look for slope over intercept. If you have high agency, move with urgency, and get energized by turning ambiguous problems into working systems — read on.

How You'll Make an Impact

Identify and own high-leverage problems

  • Embed with Operations and DevOps to surface workflow inefficiencies and translate them into scoped, buildable solutions
  • Own problems end-to-end — discovery, design, build, deploy, iterate — not just execution on a handed-down spec
  • Partner directly with team leads and the COO to prioritize work that moves the needle on speed, accuracy, and operational leverage

Build and ship AI-powered systems

  • Design and implement LLM-powered automations, agent workflows, and internal tools that reduce manual work and unlock team capacity
  • Build agentic systems that chain tasks, take actions, and integrate with HqO's internal stack — CRM, ticketing, infrastructure tooling, customer workflows
  • Deploy MCP modules and agent-to-agent frameworks where they create genuine operational leverage, not just technical novelty
  • Use AI-assisted coding tools (Claude, Cursor, Copilot) to prototype fast, gather feedback early, and iterate toward production-ready systems

Drive adoption and measure impact

  • A shipped tool that nobody uses is not a win. You'll own rollout, drive adoption, and define how success gets measured
  • Document what you build so others can maintain and extend it without you in the room
  • Surface patterns from deployments that inform HqO's broader AI Operating Model and platform direction

Raise the AI ceiling across the company

  • Help teams move from basic AI usage to structured workflows, deeper integrations, and agent orchestration
  • Extend HqO's existing foundation of 15+ deployed agents rather than starting from scratch — understand the stack, improve it, build on top of it
  • Act as a visible builder: contribute to a company culture where experimentation is the default and AI fluency is expected

What We're Looking For

We're open to a variety of backgrounds. The signal we care most about is your ability to build and ship real things with AI.


Non-negotiables

  • Demonstrated experience building something real with AI — a side project, automation, internal tool, or workflow that shipped and was used by people other than you
  • Comfort using AI-assisted coding tools (Claude, Cursor, Copilot) as a core part of your development process
  • Working knowledge of Python and/or modern scripting and backend tooling
  • Familiarity with LLM APIs, agentic patterns, and how to connect systems via APIs and webhooks
  • Ability to work on-site in Boston full-time
  • High agency: you define the problem, scope the solution, and push it forward without waiting to be told what to do next


Strong signals

  • Experience building agentic AI workflows — multi-step reasoning, tool use, orchestration, chaining
  • Exposure to RAG systems, embeddings, or vector databases
  • Experience integrating APIs or working across SaaS systems (HubSpot, Linear, Slack, Jira, or similar)
  • Familiarity with MCP modules or agent-to-agent communication frameworks
  • Exposure to frontend or full-stack development — you can build a lightweight UI when the problem calls for it
  • Background in SaaS, PropTech, or B2B operations is a plus but not required
  • Computer Science degree not required — portfolio of shipped work matters more


Who you are

  • You move with urgency. You don't wait for perfect information or a fully scoped brief before starting
  • You ship. Not demos. Not prototypes that live forever. Working systems that people rely on
  • You think about adoption, not just functionality. A tool that gets used is better than a tool that's technically impressive
  • You're honest about tradeoffs. You can articulate why you made a design choice and what you'd do differently next time
  • You operate well in ambiguity and at a company where there is no team around you — you are the team

Why This Role Matters

At HqO's scale, one highly capable Applied AI Engineer can materially change how the entire company operates. You won't be one of many — you'll be the person who builds the internal AI layer for a company with real customers, real stakes, and ambitious growth goals.


You'll have direct access to leadership, latitude to define your own roadmap, and a foundation of 15+ production agents already deployed to build on. The problems are real, the systems are in use, and the impact is visible. This isn't a proof-of-concept role.


We're a company in an industry — commercial real estate — being fundamentally transformed by AI. The person in this role will help define how that transformation happens from the inside.

How to Apply

Submit your application with the following:


  • A 5-minute (max) video walkthrough of an AI project you've built — live demo strongly preferred
  • A completed README (use the template provided) covering your project, architecture, AI integration, and what you'd do differently


Applications reviewed on a rolling basis. Finalists will be invited to a Builder Day at HqO's Boston office on July 29th. Date subject to change


Applied AI Engineer Application - Due July 16th

README & Video Submission Template

Complete all required sections. Optional sections noted. Your video and README will be evaluated using the rubric at the end of this document.

All Application Questions & Requirements in the Questionnaire Section on the following page


Evaluation Rubric

Projects are scored out of 100 points across four categories.


Category

Points

What Evaluators Look For

Problem Framing & Real-World Impact

0–25

Good: Interesting problem with a defined audience. Candidate explains the pain point and why they chose to build it.

Great: Specific, well-scoped problem tied to a meaningful workflow. Shows product thinking: who is affected, what success looks like, why AI was the right tool, and how to quantify impact.

Technical Execution

0–35

Good: Functional solution with readable code. README covers setup. Shows end-to-end build capability.

Great: Clean, well-structured code with clear architecture decisions. Reproducible. Demonstrates thoughtful design: modularity, error handling, sensible tradeoffs. Setup instructions work out of the box.

AI Fluency: Building with AI & Using AI

0–25

Good: LLM/AI tools are central to the solution. Candidate describes how coding tools accelerated development with some reflection.

Great: Agentic patterns, RAG, tool use, or non-trivial orchestration. Candidate articulates how AI coding tools changed their process, where they hit limits, and how they adapted. Shows AI as a force multiplier at both the product and dev levels.

Communication & Documentation

0–15

Good: Video walkthrough is clear and covers core functionality. README explains solution, architecture, and setup.

Great: Video explains not just "what" but "why." README includes architecture decisions, tradeoffs, and future improvements. Candidate can speak to technical decisions for a non-technical audience.

Tiebreaker:

Builder Mindset

N/A

Did the candidate go beyond the prompt? Is there evidence of curiosity and iteration, honest reflection on what didn't work, or creative problem framing? Does this person seem like someone who would move with urgency and take initiative from day one without being asked?


PD

Boston, MA

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