Location: Miami (in-office 4 days per week)
Team: Engineering
Reports to: Head of Engineering
Why This Role ExistsShared Services' guest communication runs on two things: an AI layer that handles as much of a conversation as it safely can, and a shared-services team of hospitality-trained agents who catch what the AI shouldn't touch alone. Every day, that team hits walls in the platform they use to do the work; bugs, missing tooling, workflows that don't match how a busy overnight shift actually runs. Some of that is a quick fix. Some of it is a signal that the platform is failing at scale, and by the time it reaches Engineering it's already cost real client trust.
We don't have a layer of PMs pre-chewing every one of those signals into a spec. We're hiring an engineer who can sit close to Operations, tell the difference between a one-off bug and a systemic gap, and ship the fix with no handoff required.
The RoleYou'll report to the Head of Engineering. Priorities are set jointly with the Head of Operations, who owns the operational signal driving what gets built. You'll do two things:
- Close incoming platform tickets from Shared Services. Agents, Team Leads, and Operations report issues daily; quick fixes, workflow bugs, configuration problems. You triage, diagnose, and ship.
- Find the pattern and fix it at the source. When multiple agents report the same friction, that's not a ticket, it's a product problem. When a client complaint traces back to repeated agent failures, you ask why the platform is allowing it, and you close that gap for good.
Every ship goes through the same process as any other engineer's here: product filters for coherence, design filters for UX consistency, standard code review. This role works inside those guardrails, not around them.
What You Will Do- Own features end to end; problem framing, design, backend, frontend, instrumentation, rollout, and the follow-up fixes nobody filed a ticket for.
- Work with founders, product, and design at the whiteboard stage, before anything is written down, and help decide what's worth building.
- Build the AI surfaces of the product; prompt and agent architecture, tool calling, retrieval, guardrails, and the human-in-the-loop escape hatches that make automation safe to ship.
- Build and maintain evals. Treat "does this actually work" as an engineering artifact with a regression suite, not a vibe check before launch.
- Watch real usage. Session replays, logs, transcripts, support tickets, and customer calls. Bring back what you learn as shipped changes, not as a document.
- Own the details that make software feel good; latency budgets, token cost, empty states, error copy, loading behavior, keyboard paths. These are part of the feature, not a separate polish phase.
- Cut scope and kill things. Argue a feature is wrong before you build it well.
- Compound the team's velocity; CI, preview environments, internal tools, seed data, debugging surfaces. Leverage counts as product work.
What This Role Is Not- Not a ticket queue firefighter. That's other roles on the Operations side.
- Not a shadow engineering team. You report to and work within Engineering.
- Not an independent operator building outside the platform. Everything you ship goes through product.
Anti-Signals- You want a ticket fully spec'd before you'll touch it
- You treat "why does this keep happening" as someone else's question to answer
- You measure your work by whether you closed the ticket, not whether the pattern stopped
- Your AI/LLM experience is prompting a demo - never held to a reliability bar with a real agent depending on it at 2am
Required Experience- 4+ years of full stack (stronger on the BE) software engineering experience shipping production enterprise software
- Direct experience building internal tools, agent-facing platforms, or operational systems
- Product mindset: comfortable scoping problems, asking the right questions, and communicating/prioritizing tradeoffs
- Track record of shipping fast while working inside a product and design process
- Experience working asynchronously with distributed teams
Required Technical Skills- Strong fluency in TypeScript. We currently use:
- Next JS
- NestJS
- TypeORM with Postgres
- BullMQ
- Comfortable with agentic coding tools (Claude Code, Cursor, Replit Agent)
- API integration experience (REST, webhooks, third-party SaaS APIs)
- Prompt engineering experience with production AI systems (OpenAI, Anthropic, or similar)
Strongly Preferred- Experience building tools for contact center, customer support, or operations teams
- Short-term rental, hospitality, or property management domain knowledge
- Track record of deploying AI agents in production
How You'll Work- Reports to the Head of Engineering
- Priorities set jointly with the Head of Operations, based on operational signal
- Product decisions filter through the Head of Product
- Design decisions go through our design team
- Weekly syncs with Engineering, Operations, and Product
- Miami-based, in-office 4 days per week
