Produktni vodja za digitalne rešitve – Umetna inteligenca (UI)

📍 Job Overview

Job Title: Produktni vodja za digitalne rešitve – Umetna inteligenca (UI) (m/ž)

Company: NLB Portal

Location: Ljubljana, Slovenia

Job Type: Full-time

Category: Product Management / Digital Solutions / Artificial Intelligence

Date Posted: May 19, 2026

Experience Level: Mid-Level (2-5 years)

Remote Status: On-site

🚀 Role Summary

• Lead the strategic development and roadmap of AI-powered digital products and functionalities within the bank's digital channels, focusing on enhancing customer experience.

• Drive the implementation of AI/ML and GenAI solutions, ensuring they are user-friendly, trustworthy, secure, explainable, measurable, and compliant with regulations.

• Collaborate cross-functionally with development teams (UX/UI designers, architects, engineers), business units (product specialists, sales), and support functions (compliance, legal, risk) to deliver innovative digital banking solutions.

• Leverage data literacy and AI/ML concepts, including prompt engineering and model evaluation, to define requirements and guide the development of AI-driven features.

• Ensure all AI solutions adhere to regulatory frameworks such as the EU AI Act and relevant EBA guidelines, managing AI risk assessments and documentation.

📝 Enhancement Note: This role is positioned as a Product Manager with a strong specialization in Artificial Intelligence (AI) and its application within the digital banking sector. The title "Produktni vodja za digitalne rešitve – Umetna inteligenca (UI)" translates to "Product Manager for Digital Solutions – Artificial Intelligence (AI)". The description emphasizes a blend of traditional product management responsibilities with deep technical understanding of AI/ML/GenAI and regulatory compliance in a financial context. The inclusion of "Samostojni upravljalec ponudbe" (Independent Offer Manager) suggests a significant level of autonomy and responsibility for the entire product lifecycle.

📈 Primary Responsibilities

• Develop and own the AI functional strategy and roadmap for customer-facing digital channels (mobile and web banking), prioritizing initiatives based on customer value and business impact.

• Stay abreast of emerging trends and legislation in digital banking and AI to ensure rapid and compliant introduction of relevant customer solutions.

• Define detailed requirements and lead the implementation of AI services across all digital banking channels, including smart assistants, personalization engines, and recommendation systems.

• Plan and execute user testing, measure the impact of AI features (e.g., usage, conversions, CSAT/NPS, error reduction), and drive iterative improvements based on results.

• Prepare business justifications and Key Performance Indicators (KPIs) for new AI functionalities, and continuously monitor post-launch performance against objectives.

• Communicate and present AI functionalities to customers and key stakeholders, collaborating with marketing and support teams for successful launches.

• Ensure the responsible and compliant deployment of AI solutions by actively participating in AI risk assessments, preparing model documentation (e.g., model cards), and ensuring adherence to the EU AI Act and internal data governance standards.

• Manage the product lifecycle from ideation and development through to launch and ongoing optimization, ensuring alignment with business goals and customer needs.

• Conduct market research and competitive analysis to identify opportunities for AI-driven product innovation and differentiation.

• Foster a data-driven approach to product development, utilizing analytics and insights to inform decision-making and measure success.

📝 Enhancement Note: The primary responsibilities are heavily geared towards product strategy, AI implementation within digital banking, and regulatory compliance. The role requires not just conceptual understanding but practical experience in deploying and managing AI products in production, with a focus on user experience and measurable business outcomes. The emphasis on the EU AI Act and risk assessment highlights the critical need for compliance and responsible AI deployment within a regulated financial institution.

🎓 Skills & Qualifications

Education:

Experience:

• Minimum of 3 years of experience in digital solution development and market launch.

• Proven experience in product management for digital solutions.

• Demonstrated experience with AI/ML/GenAI products in production, understanding concepts like prompt engineering, model evaluation, model limitations, and practical application.

• Experience differentiating between ML-based solutions (recommendation systems, anomaly detection) and GenAI-based solutions (chatbots, content generation).

• Experience with A/B testing and experimental approaches for AI functionality development, including hypothesis setting, uplift measurement, and iteration based on results.

Required Skills:

• Product Management: Proven ability to define product vision, strategy, and roadmap; manage product backlog, prioritize features, and lead product development cycles.

• Artificial Intelligence (AI) / Machine Learning (ML) / Generative AI (GenAI): Strong understanding of AI/ML concepts, including prompt engineering, model evaluation, limitations, and practical production deployment. Ability to distinguish between ML and GenAI applications.

• Data Literacy & Analytics: Ability to understand data quality implications for AI solutions and formulate relevant questions for data and engineering teams. Experience with A/B testing, hypothesis formulation, and measuring uplift.

• Regulatory Compliance (AI): Knowledge of the EU AI Act (risk classification, high-risk system requirements) and relevant EBA guidelines for AI in banking. Experience with AI risk assessment and model documentation (e.g., model cards) is a plus.

• Stakeholder Management: Excellent ability to collaborate with diverse teams including development (UX/UI, architects, engineers), business units (product specialists, sales), and support functions (compliance, legal, risk).

• User-Centricity: Focus on customer needs and problem-solving; proficiency with user stories, user personas, and customer journey mapping.

• Digital Banking: Understanding of digital banking products, channels, and customer journeys.

• Agile Methodologies: Familiarity with agile development processes and practices.

Preferred Skills:

• Experience with AI risk assessment or model documentation (model cards).

• Experience in financial, banking, or other regulated environments.

• Proficiency in standard and specialized PC tools.

• Active knowledge of a foreign language.

📝 Enhancement Note: The requirements emphasize a strong blend of product management expertise, deep technical understanding of AI/ML/GenAI, and practical experience in regulated environments. The explicit mention of "AI products in production" and "GenAI-based solutions" indicates a need for candidates who can bridge the gap between theoretical AI knowledge and practical application. Regulatory knowledge, particularly the EU AI Act, is a critical differentiator.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Product Strategy & Roadmap: Showcase examples of developed product strategies and roadmaps for digital products, particularly those incorporating AI or advanced technologies. Clearly articulate the vision, objectives, and prioritization rationale.

• AI/ML Product Case Studies: Provide detailed case studies of AI/ML or GenAI products you have managed. This should include the problem statement, your role, the AI/ML/GenAI approach used, key challenges faced, technical implementation details (at a conceptual level), and measurable outcomes (e.g., user adoption, efficiency gains, revenue impact, CSAT/NPS improvement).

• User-Centric Design Artifacts: Include examples of user stories, user personas, and customer journey maps that informed product development, especially for AI-driven features.

• A/B Testing & Experimentation: Demonstrate experience with A/B testing and experimental approaches in product development, including examples of hypothesis formulation, experimental design, data analysis, and iteration based on results. Quantify the impact of optimizations.

• Regulatory Compliance Documentation: If possible, provide anonymized examples or descriptions of how you have contributed to or managed AI risk assessments, model documentation (model cards), or ensured compliance with regulations like the EU AI Act within a product context.

Process Documentation:

• Agile Development Workflows: Illustrate your experience with agile methodologies, including sprint planning, backlog refinement, user story creation, and collaboration with development teams.

• Product Launch & Iteration Processes: Detail your process for launching new features or products, including go-to-market strategies, cross-functional coordination, and post-launch monitoring and iteration cycles.

• Requirements Gathering & Specification: Showcase your approach to gathering business and user requirements, translating them into clear, actionable specifications for development teams, especially for complex AI functionalities.

• Performance Measurement & Reporting: Provide examples of how you define, track, and report on Key Performance Indicators (KPIs) for digital products, specifically for AI-driven features, demonstrating how you measure uplift and business value.

📝 Enhancement Note: A strong portfolio demonstrating hands-on experience with AI product development, user-centric design, and a quantifiable impact is crucial. Given the role's focus on AI and regulation, showcasing experience with A/B testing, risk assessment, and compliance documentation will significantly strengthen an application. The portfolio should highlight the candidate's ability to translate complex AI concepts into tangible business value and user benefits.

💵 Compensation & Benefits

Salary Range:

Benefits:

• Opportunity for professional and personal development, including access to the NLB Educational Center and the broader NLB Group learning resources.

• Potential opportunities to work within other NLB Group member companies.

• Access to recreational activities through the internal sports association.

• Numerous benefits aligned with the "Family-Friendly Company" certification.

• Work within an environment recognized with the "Top Employer" certification.

• Contribution to a sustainable future as part of an organization committed to the UN Principles for Responsible Banking.

Working Hours:

• Standard full-time working hours are expected, likely around 40 hours per week. While the role is on-site, there might be flexibility for occasional remote work or adjusted hours depending on team needs and company policy, though the primary expectation is office-based presence.

📝 Enhancement Note: The salary estimate is based on typical mid-level Product Manager roles in technology or finance sectors in Slovenia, adjusted for the specialized AI focus. The listed benefits reflect the company's commitment to employee development, well-being, and corporate social responsibility, which are attractive to professionals seeking a stable and supportive work environment.

🎯 Team & Company Context

🏢 Company Culture

Industry: Banking and Financial Services, with a strong focus on Digital Transformation and Artificial Intelligence. NLB Group is a leading financial institution in Southeast Europe.

Company Size: NLB Group is a large, established financial institution with a significant presence across multiple countries in Southeast Europe. Within Slovenia, NLB d.d. is a major employer.

Founded: NLB d.d. has a long history, tracing its roots back to the establishment of the Ljubljana Bank in 1955. The NLB Group has evolved through various stages of privatization and expansion over the decades.

Team Structure:

• The role likely sits within a dedicated Digitalization or Digital Products department, possibly with a specific AI or Innovation unit.

• You will report to a Head of Digital Products, Product Lead, or a similar senior management position overseeing digital strategy and development.

Methodology:

• Agile & Data-Driven: The team likely operates using Agile methodologies (Scrum, Kanban) for product development, emphasizing iterative delivery, continuous feedback, and adaptability.

• Customer-Centric Approach: A strong focus on understanding customer needs, mapping customer journeys, and delivering solutions that enhance user experience.

• Innovation & Technology Adoption: A proactive stance towards adopting new technologies, particularly AI, to drive digital transformation and maintain a competitive edge.

• Compliance & Responsible Practices: A rigorous approach to ensuring all digital solutions, especially AI-driven ones, adhere to strict regulatory requirements and ethical standards.

Company Website: https://www.nlb.si/

📝 Enhancement Note: NLB presents itself as a forward-thinking financial institution committed to digital innovation and responsible banking. The emphasis on employee development, customer focus, and regional responsibility suggests a company culture that values both performance and ethical conduct. The "Top Employer" and "Family-Friendly Company" certifications indicate a commitment to employee well-being.

📈 Career & Growth Analysis

Operations Career Level: This role is a mid-level Product Manager position, requiring 3+ years of experience. It's a crucial role in driving the bank's digital strategy, particularly in the rapidly evolving field of AI. The "Samostojni upravljalec ponudbe" title implies a senior individual contributor role with significant autonomy.

Reporting Structure:

• Typically, this role would report to a Head of Product, Director of Digitalization, or a similar senior leader responsible for digital product strategy and execution.

Operations Impact:

• Your work will directly influence the bank's digital customer experience, driving engagement, satisfaction, and potentially revenue through the effective implementation of AI.

• You will play a critical role in positioning NLB as a digital leader in the region by successfully launching and scaling innovative AI-powered financial products.

Growth Opportunities:

• Specialization: Deepen expertise in AI product management, specifically within the financial sector, becoming a go-to expert for AI strategy and implementation.

• Leadership: Progress to senior product management roles, leading larger product portfolios, managing multiple AI initiatives, or potentially managing a team of product owners/managers.

• Strategic Influence: Gain more influence over the bank's overall digital strategy and technology roadmap, contributing to high-level decision-making.

• Cross-functional Mobility: Opportunities to move into broader product strategy, innovation management, or even business development roles within NLB Group.

• Industry Recognition: Develop a strong portfolio and reputation that can lead to speaking engagements or thought leadership in the AI and digital banking space.

📝 Enhancement Note: This role offers a significant opportunity for growth, especially for individuals passionate about the intersection of AI, finance, and product management. The focus on a cutting-edge area like AI within a large, established institution provides a stable yet dynamic career path with ample room for specialization and advancement.

🌐 Work Environment

Office Type: This is an on-site role, indicating a traditional office environment. NLB likely provides modern, well-equipped office spaces designed for collaboration and productivity.

Office Location(s): Ljubljana, Slovenia. The specific office location will be within Ljubljana, likely in a central business district or a dedicated corporate campus.

Workspace Context:

• Collaborative Spaces: Expect modern office layouts that facilitate team collaboration, including meeting rooms, project spaces, and potentially open-plan areas.

• Technology & Tools: Access to standard office technology, high-speed internet, and the necessary software and hardware for product management, data analysis, and communication. This would include the AI/ML platforms and tools used by the development teams.

• Team Interaction: Regular face-to-face interaction with colleagues from various departments, fostering a strong sense of teamwork and enabling efficient communication and problem-solving.

Work Schedule:

• Standard working hours are expected, typically Monday to Friday. While the role is on-site, the company's "Family-Friendly Company" certification suggests a degree of flexibility may be available, or at least an understanding of work-life balance needs. The primary expectation is consistent office presence for collaboration and management oversight.

📝 Enhancement Note: The on-site nature of the role emphasizes the importance of in-person collaboration, which is often beneficial for complex projects involving diverse teams and sensitive information like AI development and regulatory compliance in financial services.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A review of your CV and cover letter, focusing on relevant experience in product management, AI/ML, and the financial sector.

• HR/Recruitment Interview: An initial conversation to assess cultural fit, motivation, understanding of the role, and basic qualifications.

• Hiring Manager Interview: A technical and strategic discussion with the hiring manager, likely focusing on your product management philosophy, AI expertise, experience with product roadmapping, and problem-solving skills.

• Panel Interview / Case Study: You may be asked to prepare and present a case study related to AI product development, market strategy, or a hypothetical AI challenge within digital banking. This will assess your strategic thinking, technical understanding, and communication abilities.

• Stakeholder Interviews: Interviews with key team members or stakeholders (e.g., AI leads, business unit representatives, compliance officers) to evaluate collaboration skills and cross-functional understanding.

• Final Interview: Potentially with a senior leader to discuss career aspirations and finalize the decision.

Portfolio Review Tips:

• Highlight AI Impact: For each project in your portfolio, clearly articulate the AI/ML/GenAI components, your specific role, and the measurable business or customer impact. Quantify results wherever possible (e.g., increased conversion rates, reduced customer service inquiries, improved user engagement).

• Showcase Problem-Solving: Detail how you identified customer needs or business problems and how AI was strategically applied to solve them.

• Demonstrate Regulatory Awareness: If you have experience with AI regulations, A/B testing, or risk assessments, make sure this is clearly presented. Explain how you ensured compliance and responsible AI deployment.

• Structure for Clarity: Organize your portfolio logically, perhaps by project type or by showcasing different skill sets (e.g., strategy, execution, analysis). Use clear headings and concise descriptions.

• Be Ready to Discuss: Prepare to walk through your portfolio in detail, answering specific questions about your contributions, decision-making processes, and lessons learned.

Challenge Preparation:

• AI Strategy & Roadmap: Be prepared to discuss how you would develop an AI strategy and roadmap for digital banking, considering customer needs, business goals, technological capabilities, and regulatory constraints.

• Product Prioritization: Practice prioritizing AI features based on value, feasibility, risk, and strategic alignment.

• AI Risk & Ethics: Review common AI ethical considerations, potential biases, and how to mitigate them. Understand the basic principles of AI risk assessment and the EU AI Act.

• Stakeholder Communication: Prepare examples of how you communicate complex technical concepts (like AI) to non-technical stakeholders and how you manage differing priorities.

📝 Enhancement Note: The interview process is likely to be thorough, assessing both technical AI knowledge and product management acumen. A well-prepared portfolio that demonstrates practical AI product experience, strategic thinking, and an understanding of regulatory requirements will be critical for success. Be ready to articulate the "why" and "how" behind your AI product decisions.

🛠 Tools & Technology Stack

Primary Tools:

• Product Management Platforms: JIRA, Confluence, Asana, Aha!, or similar for backlog management, roadmap planning, and documentation.

• Collaboration Tools: Microsoft Teams, Slack, or similar for daily communication and team coordination.

• Prototyping & Design Tools: Figma, Sketch, Adobe XD for UX/UI design collaboration and review.

Analytics & Reporting:

• Web & Mobile Analytics: Google Analytics, Adobe Analytics, or similar for tracking user behavior and feature adoption.

• BI & Data Visualization Tools: Tableau, Power BI, Qlik Sense for creating dashboards, analyzing performance data, and identifying trends.

• A/B Testing Tools: Optimizely, VWO, or internal A/B testing frameworks for experimentation.

CRM & Automation:

• CRM Systems: Salesforce, Microsoft Dynamics, or a similar enterprise CRM for customer data management (though less direct usage for this role, understanding its integration is key).

• Data Warehousing & Databases: Experience with querying data from SQL databases or data warehouses (e.g., Snowflake, BigQuery, Redshift) to inform product decisions.

• AI/ML Platforms & Services: Familiarity with cloud-based AI/ML platforms (e.g., AWS SageMaker, Azure ML, Google AI Platform) and specific AI/ML libraries or frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) will be beneficial. Understanding of prompt engineering interfaces and tools.

📝 Enhancement Note: While the role is Product Management, a strong understanding of the underlying technology stack, especially AI/ML platforms and data analytics tools, is crucial for effective collaboration with engineering and data science teams. The ability to interpret data from these systems and translate requirements for them is key.

👥 Team Culture & Values

Operations Values:

• Customer Centricity: A core value focused on understanding and meeting customer needs, ensuring digital solutions enhance their banking experience.

• Innovation & Agility: A drive to embrace new technologies like AI and adapt quickly to market changes, fostering a culture of continuous improvement.

• Collaboration & Teamwork: Emphasis on working together across departments to achieve common goals, valuing diverse perspectives and open communication.

• Responsibility & Integrity: A commitment to ethical practices, data privacy, and regulatory compliance, especially critical in the financial sector and with AI deployments.

• Data-Driven Decision Making: Utilizing data and analytics to inform product strategy, measure success, and drive continuous optimization.

Collaboration Style:

• Cross-Functional Integration: Seamless collaboration between product, engineering, design, data science, marketing, compliance, and business units is essential for successful product development and launch.

• Open Communication: A culture that encourages open dialogue, constructive feedback, and transparent information sharing.

• Agile Mindset: Embracing iterative development, flexibility, and a willingness to adapt plans based on new insights or changing requirements.

• Knowledge Sharing: A proactive approach to sharing insights, best practices, and lessons learned across teams to foster collective growth and efficiency.

📝 Enhancement Note: The company culture appears to be a blend of traditional financial sector discipline (responsibility, integrity) with a modern, forward-looking approach to digital transformation and employee well-being. Success in this role will require strong interpersonal skills and the ability to navigate a complex stakeholder landscape.

⚡ Challenges & Growth Opportunities

Challenges:

• Balancing Innovation with Regulation: Effectively integrating cutting-edge AI technologies while strictly adhering to financial regulations and the EU AI Act.

• Data Quality & Availability: Ensuring access to high-quality, relevant data to train and deploy effective AI models in a secure manner.

• Cross-Functional Alignment: Managing diverse stakeholder expectations and priorities to ensure cohesive product development and strategic alignment.

• Rapidly Evolving AI Landscape: Keeping pace with the fast-changing field of AI and identifying which advancements are truly valuable and feasible for the bank.

• User Trust & Explainability: Building and maintaining customer trust in AI-driven features, particularly ensuring transparency and explainability where required.

Learning & Development Opportunities:

• AI Specialization: Deepen expertise in specific AI domains relevant to finance (e.g., fraud detection, personalized financial advice, risk modeling) through formal training and hands-on project work.

• Product Strategy & Leadership: Develop advanced product strategy skills, potentially leading larger product initiatives or teams, and gaining exposure to executive-level decision-making.

• Regulatory Expertise: Become a subject matter expert in AI governance and compliance within the financial sector, a highly valuable and in-demand skill.

• Industry Engagement: Attend relevant conferences, webinars, and join professional communities to stay updated on AI trends, best practices, and network with peers.

• Mentorship: Benefit from mentorship from senior leaders within NLB Group and potentially external industry experts.

📝 Enhancement Note: The challenges are significant but also represent substantial growth opportunities. Navigating the complexities of AI in a regulated industry like banking requires a unique skill set that, once mastered, offers a strong competitive advantage and career progression.

💡 Interview Preparation

Strategy Questions:

• "How would you develop a product roadmap for AI-driven personalization features in a mobile banking app, considering both customer value and regulatory constraints?"

• "Describe a time you had to balance ambitious AI innovation with strict compliance requirements. What was your approach?"

• "How do you prioritize features for an AI product when faced with limited data or development resources? What frameworks do you use?"

Company & Culture Questions:

• "What excites you most about applying AI in the banking sector, and specifically at NLB?"

• "How do you approach collaborating with technical teams (AI engineers, data scientists) and non-technical teams (marketing, sales)?"

• "Given NLB's commitment to responsible banking, how would you ensure our AI initiatives align with these values?"

Portfolio Presentation Strategy:

• Quantify Everything: For each project, be ready to present clear metrics on user adoption, engagement, conversion rates, efficiency gains, or cost savings attributed to your product.

• Focus on AI Impact: Clearly articulate the AI/ML/GenAI components, your specific role in their implementation, and the tangible business value they delivered.

• Address Challenges & Learnings: Be prepared to discuss challenges encountered during product development and how you overcame them, highlighting lessons learned and how they informed future decisions.

• Showcase Regulatory Acumen: If applicable, highlight how you ensured compliance, managed risks, or documented AI models.

• Structure for Clarity: Use a clear narrative structure for each case study: Problem -> Solution (Your Role & AI Approach) -> Results (Metrics) -> Learnings.

📝 Enhancement Note: Prepare to demonstrate a strong understanding of both product management principles and the specific nuances of AI in finance. Your ability to articulate strategy, manage complex cross-functional relationships, and quantify impact will be key. Practicing your portfolio presentation with a focus on AI and regulatory aspects is highly recommended.

📌 Application Steps

To apply for this operations position:

• Submit your application through the provided link on the NLB careers site by May 29, 2026.

• Tailor your CV: Highlight experience in product management, AI/ML/GenAI, digital banking, and any experience within regulated industries. Quantify achievements with specific numbers and metrics.

• Craft a compelling cover letter: Clearly articulate your passion for AI in finance, your understanding of the role's responsibilities, and how your skills and experience align with NLB's values and the specific requirements of this Product Manager position.

• Prepare your portfolio: Curate examples of your past work that showcase AI product development, user-centric design, strategic roadmapping, and measurable results. Be ready to present 1-2 key projects in detail during interviews.

• Research NLB Group: Familiarize yourself with NLB's digital strategy, recent innovations, and their commitment to responsible banking. Understand their market position and competitive landscape in Southeast Europe.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.