Jobbing Builder

Sherpas; Málaga; Presencial; EUR 60.000 - 90.000; Jornada completa

Descripción de la vacante

Sherpas is building AI-enabled financial advisory tools. The role sits between insight and shipped product, turning observations into structured, testable specifications that engineers can implement without back-and-forth clarifications.

You will own the journey from idea to shipped feature, including release notes and enablement material, with a heavy emphasis on AI-driven prototyping and rigorous acceptance criteria.

Formación

• Fluent English and Spanish.
• Experience owning a product area on a complex, data-heavy B2B product.
• Able to write precise acceptance criteria that are testable.
• Able to translate user observations into concrete specs for engineers.
• Experience in financial services or a regulated domain.

Responsabilidades

• Conception: generate and sharpen ideas using AI, propose three structured options with a recommendation.
• Definition: turn approved direction into precise, testable specs; anticipate questions.
• Deep product knowledge of our advisor workflow and where the request fits.
• Release enablement: write release notes and client-facing material on day one.
• Unblock roadmaps by diagnosing why items stall and driving resolution.

Conocimientos

AI tooling usage

wealth management domain

data-heavy B2B product ownership

precise specification writing

user observation to specification

English/Spanish fluency

Herramientas

Cursor

Claude

ChatGPT

Descripción del empleo

Most product roles start at the spec. This one starts at the idea — and you won't wait for someone else to hand it to you. You'll use AI to compress the distance between a rough observation and a shippable concept, then drive that concept all the way to a definition an engineer can build from without guessing.

We're building AI agents that automate the invisible labor of financial advice. The product surface is complex, the domain is regulated, and the leverage of getting it right is enormous. We need someone who is genuinely excited about AI as a building tool — not as a buzzword to add to a CV.

What this role actually is

You sit between raw insight and shipped product. That means two things that most people treat as separate jobs:

• Conception. You generate and sharpen ideas, not just receive them. You use AI — aggressively — to prototype concepts, stress-test assumptions, explore edge cases, and pressure-check requests before they become roadmap. When someone says "we should do something about X," you come back with three structured options and a recommendation, not a question about requirements.
• Definition. You turn the approved direction into specifications that are precise enough to build from and specific enough to test. Ambiguity in a spec is a defect. Engineers should not be asking clarifying questions mid-build — because you anticipated them.

What you will own

• Idea sharpening. A rough signal from a client call, a sales conversation, or a competitor move — you pick it up, run it through structured analysis, and return a framed proposal: the problem, the options, the tradeoffs, a recommendation.
• Functional definition. Acceptance criteria that are actually testable. Edge cases that are actually covered. A spec that reads like it was written by someone who has thought about every state the feature can be in.
• Deep application knowledge. You will know our product and the advisor workflow it serves better than almost anyone — well enough to spot when a request is really a symptom of a different problem.
• Route to market. A feature isn't done when it ships. You write the release notes, the enablement material, and the explanation the client-facing team needs on day one.
• Unblocking. When something has been sitting in the roadmap for two months, finding out why is your job.

What we are looking for Must have

• You use AI tools every day — not occasionally. Cursor, Claude, ChatGPT, whatever gives you leverage. You have opinions about what works and what doesn't.
• You have real working knowledge of wealth management, financial advisory, and financial planning — not as background reading, but as the lens through which you evaluate every product decision.
• You have owned a product area on a complex, data-heavy B2B product — from concept to shipped.
• You write with precision. You treat a vague requirement as a problem to solve, not a starting point to accept.
• You can sit with a user and watch them work, then translate what you saw rather than what they said.
• Fluent English and Spanish: our team works in both, our users work in one.
• You have used AI to generate prototypes, wireframe concepts, or structure functional designs — not just drafts.
• Financial services, wealth management, or another regulated domain.
• Experience writing enablement and release material, not just specifications.
• To be an engineer. You need to be precise enough that an engineer can build from what you write.
• To wait for permission to have an opinion on what the product should do next.

Boundaries, stated plainly

• Client Success owns adoption of what exists. You own definition of what doesn't exist yet.
• You write acceptance criteria; QA verifies them. Defining and verifying should not be the same person.
• Engineering decides how to build it. You decide, precisely, what it needs to do.

What success looks like at 6 months

• You're generating product ideas that make it to the roadmap — not just processing requests from others.
• Engineers stop asking clarifying questions mid-build, because the spec anticipated them.
• Releases arrive with their enablement material already written.
• Features move from roadmap to shipped at a visibly higher rate.

How we hire

• A conversation about a product area you've owned and how you drove it from idea to shipped.
• A practical exercise: we give you a real half-formed observation from our own product — you come back with a structured proposal and a spec.
• A working session with product and engineering.