PAIR Finance was founded in Germany in 2016 with a clear vision: to make debt collection in Europe more digital, efficient, and customer-centric. We believe that collecting effectively and treating people with respect are not opposites - they go hand in hand. Our AI-driven approach sets us apart from traditional providers, especially in the amicable collection phase, where we focus on resolution over confrontation.

• Experience in B2C customer service, with a background in receivables management or debt collection.
• A hands-on, solution-focused approach and a genuine passion for helping customers.
• Comfort working in a fast-paced environment where processes evolve and continuous improvement is the norm.
• Business-fluent communication skills in Norwegian and English - both written and spoken.
• Solid MS Office skills and an open, enthusiastic attitude towards new technologies, including AI.
• Alignment with our values: Transparency, Execution, Ownership, Customer Centricity, Innovation, and Integrity.

• a degree in Data Science, Computer Science, Mathematics or similar
• experience with machine learning frameworks (e.g. pytorch, scikit-learn, transformers)
• hands-on experience with deployment of (ideally open source) LLMs (hosting, fine-tuning, prompt engineering, evaluation)
• experience with Reinforcement Learning 
• experience with cloud-based infrastructure solutions, such as AWS

• Demonstrable experience in Artificial Intelligence/Machine Learning security in a production context – not just general cybersecurity.
• Practical knowledge of LLM-specific risks, such as:prompt injection and jailbreaks, data leakage and sensitive information exposure, model inversion, membership inference, supply chain risks in AI tooling and models.
• Solid understanding of the ML lifecycle and typical MLOps setups (data pipelines, training, evaluation, deployment, CI/CD, monitoring) and where to place security controls.
• Experience designing or reviewing secure architectures for AI/LLM systems, including: API security and authentication/authorization, secrets management (API keys, tokens, credentials), isolation of tenants/contexts and access control for data sources & vector stores, protection of sensitive data in prompts, logs and training data.
• Experience working side-by-side with data scientists or ML engineers – you have credibility in technical rooms and can challenge design decisions constructively.
• Ability to read Python code and basic ML pipelines and to build small scripts/tools (e.g. for automated tests, log analysis, or prototype guardrails).
• Background in risk assessment and in writing or reviewing policy and governance documentation.
• Familiarity with relevant AI standards and frameworks, such as: ISO 42001, OWASP LLM Top 10, NIST AI RMF, OECD AI Principles.
• Understanding of EU AI Act obligations and how they apply to a fintech / financial services context, with the ability to map them to concrete controls.
• Strong grasp of data protection and privacy-by-design in AI (data minimisation, pseudonymisation/anonymisation, retention and deletion of training and log data)

• Experience reviewing AI vendor contracts or working with procurement/legal on technology and SaaS agreements.
• Prior audit or regulatory experience, ideally representing technical systems to auditors or financial regulators.
• Experience with logging, monitoring and incident response for AI or other high-risk systems.
• Background in financial services or fintech, or another highly regulated industry.

• Ability to translate technical AI risk into clear business language – you’re comfortable presenting to both engineers and senior leadership.
• Comfort with ambiguity – AI regulation, standards and best practices are evolving quickly, and you help us navigate that.
• Collaborative, enabling mindset – you work through influence, coaching and partnership, not gatekeeping. You help teams ship valuable AI solutions safely, not stop them.