Product Manager, AI & Automation

Product Manager, AI & Automation | Collective Edge | Enterprise-wide (Collective Edge, Royal Ambulance, Apex Paramedics) Role Overview Collective Edge is hiring a Product Manager, AI & Automation to find manual, labor-intensive work across our businesses and turn it into simpler, more effective workflows. You’ll work with teams at Collective Edge, Royal Ambulance, and Apex Paramedics to understand friction points and daily workflow challenges, then build and test practical technology and AI-enabled solutions, and make sure the improvements stick. Building on our existing Slack-connected AI agent and API integrations with operational platforms, you’ll identify opportunities to streamline workflows across teams and departments. You’ll find the manual, repetitive, labor-intensive work happening across the business, make the case for fixing it with real numbers, redesign the workflow, and get it into the hands of the people who’ll run it every day. You’re equal parts process detective, AI/automation builder, and change partner to the operators who know the work best. Working mantra: observe, document, simplify, digitize, automate, measure, teach. What You’ll Own Process discovery. Shadow and interview the people doing the work. Document how it actually happens: workflows, handoffs, data sources, exceptions, and workarounds. Quantification. Put real numbers on a workflow’s cost across labor, capacity, speed, quality, and service, and set a baseline you can measure against after launch. Prioritization. Assess assigned opportunities, rank them by impact and feasibility, and make clear recommendations to the Transformation Partner and executive team. Portfolio management. Maintain a focused portfolio, sequence work based on impact and readiness, and make trade‑offs explicit when demand exceeds capacity. Redesign and delivery. Design, configure, and prototype AI, automation, and no-code/low‑code solutions in partnership with our BI/engineering team and functional owners: tools, dashboards, agent-based workflows, trackers. Bring hands‑on building ability, while BI/engineering provides the technical partnership needed to develop, integrate, and productionize solutions. This role is accountable for moving the work from operational problems through a validated solution, not for serving as the sole technical builder. Adoption. Train and support the teams who’ll use what you build. Test with real users, iterate, and make sure it actually gets used: no shelfware. Ownership transfer. Prototype and validate solutions, then transition ongoing ownership to the right functional team. Partner with BI or engineering when production deployment, system integration, or ongoing technical support is required, with clear roles and a documented handoff. Playbook building. Turn each project into a repeatable method so the capability gets faster and stronger over time, across every part of the business. Technical Environment You don’t need to be a software engineer, but you do need to be comfortable working in a modern, cloud‑based, AI‑first environment. Our stack is built on: Cloud infrastructure: AWS, plus edge and web platforms such as Cloudflare. Version control and delivery: GitHub, with pull requests and automated CI/CD pipelines. AI and automation: LLM‑based assistants and agents (Claude and similar), including our existing Slack‑connected AI agent, integrated with internal tools and operational platforms through APIs. Data and integrations: REST APIs, SQL databases, and integrations with operational SaaS systems (dispatch, billing, HR, fleet, finance). Collaboration: Slack and Google Workspace. Compliance: a healthcare environment with HIPAA/PHI data‑handling requirements. What Success Looks Like In your first 90 days, you will: Assess the pipeline. Build a fact‑based inventory of assigned transformation opportunities, including the problem, operational value, complexity, dependencies, functional owner, and readiness. Establish prioritization. Recommend and secure approval for a repeatable method based on impact, feasibility, strategic alignment, risk, and capacity. Build an approved portfolio. Convert the pipeline into an approved near‑term portfolio with clear sequencing, sponsors, decision rights, and resource requirements. Launch the first pilot. Lead the design, build, and testing of at least one working prototype that addresses a meaningful operational problem, partnering with BI/engineering and the functional owner rather than operating as the sole builder. Define the baseline and measurement plan. Establish the current‑state baseline, expected benefit, adoption measures, quality safeguards, and review cadence for the pilot. Assign ongoing ownership. Name a functional owner for adoption and ongoing performance, with a documented handoff plan to the function, BI, or engineering. Beyond that, success looks like: a growing portfolio of workflows that are measurably faster, cheaper, or higher‑quality than before; functional leaders who’ve genuinely adopted what you built and own it going forward; and a repeatable playbook that makes the next project easier than the last. Qualifications Required experience and capabilities: 6-9 Years of demonstrated experience taking operational improvements from process discovery through prototype, implementation, adoption, and measurable results. Strong analytical thinking for breaking down complex, cross‑functional workflows, and excellent written and verbal communication. Hands‑on experience using AI tools (LLM assistants, agents, automation) to prototype and improve real workflows, and good judgment about when a prototype is ready to hand to engineering. Working familiarity with cloud platforms (AWS or similar), GitHub, APIs, and SQL, enough to collaborate effectively with engineers, read a spec or query, and test what comes back. Strong spreadsheet and data skills: define a metric, trace it to its source, set a baseline, and measure results. Software engineering experience is not required, but you must be able to turn an operational problem into a working prototype and partner with BI/engineering for production deployment. Comfortable with ambiguity: asks sharp questions, synthesizes quickly, and produces usable work without perfect instructions. Preferred, but not required: Experience in healthcare, or another environment with regulated data (HIPAA or similar), multi‑site operations, or a formal transformation function. You’ll thrive in this role if you are: Driven: curious, resilient, self‑propelled, and energized by ambiguity. A clear thinker and structured communicator who can explain technical or process ideas to non‑technical operators. A good human: kind, humble, and trustworthy enough to sit beside long‑tenured operators without making them feel replaced. A team player who gives credit and learns from the subject‑matter experts around you. Someone with practical judgment about AI and automation: you treat them as tools in service of business value, not the answer to everything. About Collective Edge Collective Edge unites leading ambulance and medical‑transport companies, including Royal Ambulance and Apex Paramedics, under shared leadership, systems, and infrastructure. Each operating company stays community‑facing under its own name and leadership; Collective Edge provides the shared services (Finance, Business Intelligence, People, Communications, and more) that let each one get stronger together than it could on its own. Work Model This is a hybrid role supporting locations across California and Colorado, with approximately 25% travel to current and future company locations. #J-18808-Ljbffr Collective Edge