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Product Discovery & Prototyping Engineer

Braiins
CompanyBraiins
CategoryEngineering
LocationPrague
RemoteHybrid
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted13 Jul 2026
Last verified2 Aug 2026
SourceEmployer ATS (ashby)
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Description
✨ WHAT AWAITS YOU HERE: As a Product Discovery & Prototyping Engineer, you will help us quickly explore, validate, and shape new product ideas across Braiins Pool, Hashpower, and related products. You will work as a close partner to the product owner, turning business ideas, user problems, requirements, and early designs into clear specifications, experiments, clickable or functional prototypes, and validated product proposals. This role combines analytical thinking, product discovery, data analysis, requirements definition, communication with design and engineering teams, and AI-assisted prototyping. You do not need to be a full-time production developer from day one, but you should be comfortable learning technical tools, using AI responsibly, and building lightweight prototypes that help us decide what is worth building properly.     🤝 KEY RESPONSIBILITIES: - Work closely with the product owner to explore, structure, and validate new product and feature ideas. - Translate business goals, customer problems, and stakeholder input into functional and non-functional requirements. - Create product discovery materials such as problem statements, user stories, acceptance criteria, flows, edge cases, validation plans, and decision records. - Use AI-assisted development and prototyping tools to create quick experiments, mockups, clickable prototypes, scripts, dashboards, or lightweight functional prototypes. - Cooperate with design, backend, frontend, QA, support, and data-oriented stakeholders to clarify feasibility, user value, expected impact, and operational consequences. - Help verify product viability before full engineering investment: user value, complexity, dependencies, supportability, risks, and measurable success criteria. - Query and interpret data from telemetry databases to help to validate ideas. - Document findings clearly so engineering teams can continue from validated discovery into implementation. - Actively improve our discovery and prototyping process, including reusable templates, AI-assisted workflows, and feedback loops. - Use AI tools responsibly to accelerate research, implementation, testing, documentation, automation, and delivery while keeping strong human ownership, review, security, and production quality   🔎 WE ARE LOOKING FOR SOMEONE WITH: - Mid/Senior experience in product analysis, business & data analysis, product ownership, requirements engineering, technical analysis. - Strong analytical thinking and ability to structure ambiguous ideas into clear problems, requirements, assumptions, and next steps. - Experience defining functional and non-functional requirements, acceptance criteria, user flows, edge cases, and product validation approaches. - Ability to communicate with product, design, engineering, QA, support, and business stakeholders. - Ability to query SQL-like queries and interpret data. - Comfort working with technical products where product decisions must consider data flows, operational behavior, constraints, and customer workflows. - Interest in learning AI-assisted prototyping, lightweight coding, scripting, or no-code/low-code tools if you do not already use them. - Strong ownership, curiosity, and ability to move quickly without losing clarity or discipline. - Willingness to understand Bitcoin mining, pool operations, hashpower products, and customer workflows.   💪 NICE TO HAVE: - Previous experience with product discovery, technical product management, UX collaboration, or early-stage feature validation. - Experience creating prototypes, internal tools, scripts, dashboards, clickable mockups, or AI-assisted proofs of concept. - Experience with SQL, APIs, data analysis, Figma, Git, Python, TypeScript, or similar tools. - Experience with Bitcoin, cryptocurrencies, mining, fintech, trading, infrastructure, or B2B technical products. - Ability to connect qualitative user feedback with quantitati