Product Manager, Operational Excellence - AI Technologies, Proccess Automation
Software Engineering, Product, Data Science
Barbados · Mexico · Dominica · Dominican Republic · Haiti · Jamaica · South America · Central America · Cuba · Antigua and Barbuda · The Bahamas · Belize · Guyana · Grenada · St Kitts & Nevis · St Vincent and the Grenadines · Suriname · St Lucia · Trinidad and Tobago · Remote
Posted on Oct 24, 2026
Requirements
Must-haves
- 4+ years of product management or business operations experience
- Experience with no-code/low-code platforms, automation tools, and AI-powered workflows
- Experience working cross-functionally with non-technical stakeholders
- Ability to identify operational problems and deliver practical solutions
- Ability to work as a solo contributor without a large team or an established playbook
- Ability to prioritize working solutions and existing tools over building from scratch
- Ability to balance a long-term vision with short-term execution
- Deep understanding of how problems in one team affect the rest of the company
- Strong communication skills in both spoken and written English
What makes you stand out
- Proven internal-ops wins: you found a real operational bottleneck, shipped a fix, and can describe the result in numbers (e.g. hours saved, faster cycle times, fewer manual handoffs, etc.).
- Solo operator at a scaling company: you’ve been the only person, or one of very few, owning internal systems at a startup or scale-up during a growth phase.
- Range across business teams: you’ve worked with at least two or three of CS, Sales, Marketing, and Finance, and can speak to each team’s metrics and pain points.
Nice-to-haves
- Startup experience
- Bachelor’s Degree in Computer Engineering, Computer Science, or equivalent
What you will work on
- Review how CS, Sales, Marketing, and Finance operate today to find friction and build or source fixes
- Define and own the internal AI roadmap, finding where AI can cut repetitive work and improve decisions
- Implement solutions without engineering resources (e.g. no-code tools, low-code automation, AI workflows, off-the-shelf products, etc.)
- Work closely with CS, Sales, Marketing, and Finance to understand their workflows, pain points, and capacity limits
- Spot team needs early and proactively surface the problems worth solving
- Partner with engineering on custom builds, writing requirements and owning delivery
- Connect business teams with product and engineering, turning operational needs into actionable solutions
- Design systems and processes that can support a company twice the current size