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Responsibilities
- Manage the people on the software development team with the objective of coaching and developing our colleagues (individual development plans), conducting 1:1 sessions, setting action plans and providing frequent feedback.
- Guide team members in the use of agile practices, facilitating ceremonies that are part of the squad’s methodology such as plannings, refinements, retrospectives, etc.
- Remove impediments for the team.
- Foster an environment of respect and trust together with team members, adapting your leadership style to different situations.
- Navigate the company, identifying opportunities and key roles for the team’s success.
- Coordinate initiatives that require one or more teams for the product’s success.
- Hold sessions with stakeholders to present recent results, gather feedback/insights and align on the product roadmap.
- Ability to present complex technical information clearly and concisely to all types of stakeholders.
- Build the squad’s vision and mission together with team members.
- Regularly monitor product metrics, business metrics and technical indicators—critiquing, improving and providing visibility into the team’s objectives and the status of initiatives.
- Participate in product discovery processes, problem mapping and incident resolution.
- Contribute to the definition of objectives and key metrics for the product/squad, frequently presenting these results to stakeholders (OKRs).
- Establish a software development process and maintain a steady, healthy delivery rhythm.
- Handle competing needs/priorities, taking on responsibilities and risks in a fast-paced and constantly changing context.
Qualifications
- Previous experience leading software development teams for digital products.
- Knowledge of facilitation techniques and problem-solving methods.
- Experience working in agile teams (Scrum, Kanban, etc.).
- Leadership experience during technology and/or process modernization or migration projects.
- Previous experience with or deep knowledge of Generative AI (GenAI) projects, large language models (LLMs) and agentic tools.
- Strong technical background (former developer or architect) with the ability to discuss software architecture, integrations and engineering best practices.
- Familiarity with AI frameworks (e.g., LangChain) and understanding of how language models operate (for technical management purposes, not necessarily hands‑on).
- Hands‑on, data‑oriented profile: autonomy to analyze scenarios and make decisions based on indicators.
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