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Porto, Portugal
Hybrid
Not Available
AI fluency is a core expectation at Sword Health. Every candidate is assessed against our three-level framework — be ready to share real examples of how AI is already part of how you work.
Explorer (Level 1) — Uses AI daily to boost personal productivity
Builder (Level 2) — Creates workflows and tools that elevate the whole team
Integrator (Level 3) — Embeds AI into products and processes at scale
Every hire must demonstrate at least Level 1. The expected level will vary depending on the seniority of the role.
Own product definition through delivery for new features and initiatives in your area, defining the user, their struggle, and what a successful solution looks like;
Partnering with technical and non-technical stakeholders to properly scope those initiatives, by deep-diving into the underlying pain points, assessing the feasibility and scalability of proposed solutions, defining requirements, and acceptance criteria;
Support execution & iteration by working with other teams (Engineering, Product, Clinical, Operations) in tight feedback loops to make sure requirements are met, scope is adjusted as new information comes in, and development does not drift away from high-value product experiences;
Act as a strategy thought-partner: bring proposals and feature ideas to the Head of Product, and help explore, prioritize, and test them;
Communicate progress, learnings, and strategic recommendations clearly to leadership and cross-functional partners;
Use AI as a first-class tool in how Pulse itself is built, and increasingly, in how you work — Pulse leans on AI/LLM-driven features (Phoenix), so fluency with what's possible (and its limits) matters.
5+ years of experience in product management, ideally including consumer-facing digital health, wellness, or another B2C space with real behavior-change/retention dynamics;
Comfort owning ambiguity without a nearby manager: this role is the senior-most product judgment physically in the room with the build team;
Technical fluency: able to go deep with engineering on architecture and tradeoffs; comfortable with AI/LLM-powered product concepts even if you don't code yourself;
Strong written and verbal communication;
Data fluency: hypothesis-driven, comfortable defining metrics and reading dashboards to judge feature success (BigQuery/Looker experience a plus);
Bias for action and a real ability to disagree upward when the data or the team's read on the ground contradicts the plan.
Have experience working in a fast-paced environment wearing different hats, acting scrappy when the situation calls for it;
Experience in healthcare or clinical products, with cardiometabolic focus as a bonus;
A track record of being the "glue" person on a cross-functional team.