Descripción de la oferta
About Us Quadrivia is the health technology company behind Q, a comprehensive, controllable, and customizable assistant AI built by clinicians, for clinicians. Addressing the urgent shortage of healthcare professionals, Q provides real-time, personal, and reliable support for clinical tasks across the care continuum. Designed for providers, payers, and pharmaceutical companies, Q is easy to customise and integrates seamlessly into workflows, delivering precise assistance across the care spectrum. Compruebe que cumple con los requisitos de habilidades para este puesto, así como con la experiencia asociada, y luego envíe su CV a continuación. The Role At Quadrivia, we’re solving the chronic imbalance between the growing demand for healthcare and the constrained supply of clinical skills. While we’re building the world’s most comprehensive clinical assistant externally, internally we’re pioneering a new way to run a company. We believe that by letting AI agents handle the repetitive, necessary tasks that bog down every business, we can free our brilliant minds to focus on what truly matters. That is where you come in. We’re looking for an AI Automation Engineer to build an ambitious autonomous backbone for our operations. If you’ve spent the last year deep in Skills, workflows, and MCP architectures—orchestrating autonomous flows with Claude, Gemini, and the latest agentic toolchains—and you know exactly where the line sits between a prototype and a production-grade system, you’ve found your team. What You'll Do Hunt down high-leverage processes. Talk to people across the company, find the manual, repetitive, error-prone work, and rank it by what's genuinely worth automating. Pull a workflow out of someone's head and specify it. Most of the job is turning a vague "this is just how we do it" into something precise enough to automate. Build the automation. Python and API glue, MCP servers and clients, Claude Skills, agent workflows, and small services where they're needed. Instrument what you ship so it doesn't rot silently. Logs, alerts when something breaks, and a way to know whether the automation is still doing its job. Drive adoption. Get non-technical teams to trust and use what you've built, train them, and stay close after launch so it sticks. Know when to escalate. When an automation needs to become real platform, hand it to the backend team instead of bolting on. Knowing where that line sits is part of the job. Minimum Qualifications You've automated real business processes end to end, from "what's the actual problem here" through to people using it every day. We'll want to see what you shipped and what it saved. You're comfortable in front of non-technical teams. You can extract a workflow, push back on a bad priority, and sell a new way of working to people who don't code. You write code. Python, APIs, scripting, enough to build the automation yourself without waiting on an engineer for every step. You're fluent in the agentic toolchain (Claude Cowork, Skills, MCP, workflow tools), or you'll obviously get there fast. You instrument and maintain what you build. You've felt the pain of an automation that broke quietly, and you don't let it happen twice. Nice to Have Startup experience, and comfort wearing several hats. A background as a solutions engineer, technical PM, consultant, or ops engineer who went agentic-native. Classic RPA exposure (UiPath and similar). Useful for context, as some legacy systems and EHRs can only be accessed via these integration types. Healthcare or other regulated-industry experience. Spanish, for the internal teams you'll embed with. Example Problems You'll Tackle GTM & Sales Intelligence: Automate CRM updates, call logging, deal qualification, prospect research, and smart alerting to keep the team selling instead of doing admin. Content: Automate social media workflows, using AI to streamline video generation and post-production editing. HR: Streamline candidate screening workflows and automate repetitive tasks in the employee onboarding process. Ops: Map high-effort manual processes, like patient onboarding, and build automations to handle the heavy lifting. Platform: Graduate successful scripts into the core backend platform whenever an automation outgrows its initial scope. Tech Stack Python, REST and webhook integrations, MCP, Claude Skills and Cowork, agent and workflow orchestration, plus whatever automation tooling fits the job. You'll lean on the AI platform (Cortex) for anything heavy, and pick up new tools about as fast as they ship. What Success Looks Like Measurable hours given back across the company, on the processes people used to dread. The teams you work with reach for automation by default and trust it, because the things you ship keep working. xbhjioe Your automations are instrumented and maintained, not a graveyard of scripts nobody dares touch. Quadrivia runs leaner than its headcount suggests, and you're a big reason why.
