Design and build Generative AI applications, leveraging modern techniques such as RAG (Retrieval-Augmented Generation)
Build and deploy agentic AI systems capable of multi-step reasoning, planning, and tool us
Integrate external tools, APIs, and enterprise data using Model Context Protocol (MCP)
Work with embedding models, chunking strategies, and vector stores to enable efficient information retrieval
Build and optimize data pipelines tailored for AI use cases, from ingestion to model interaction
Leverage Microsoft Azure services to develop scalable, cloud-native AI solutions
Integrate AI solutions into production, including:
Model versioning and lifecycle management
Monitoring (performance, drift, usage)
Continuous improvement workflows
Collaborate closely with data engineers, software engineers, and business stakeholders to deliver end-to-end AI solutions
Ensure solutions are built with security, compliance, and governance in mind
Contribute to agile development practices and continuously improve ways of working
Play a key role in accelerating AI adoption and delivery across the bank
Strong programming skills in Python, with experience building AI/ML or Generative AI applications
Hands-on experience with: LLMs and Generative AI frameworks, RAG architectures, embeddings, and vector databases API-based model integration and application development
Experience in implementing agentic AI systems (agent orchestration, planning, memory, tool usage)
Understanding of Model Context Protocol (MCP) for connecting LLMs to tools, data sources, and services
Experience working in cloud environments (preferably Microsoft Azure)
Understanding of: Model lifecycle and MLOps principles, Monitoring and improving AI system performance and Responsible AI and secure handling of sensitive data
Creative problem-solving capabilities coupled with critical thinking skills; proven track record of addressing complex challenges through innovative solutions. Commitment to exploring new methodologies that advance AI application capabilities.
Ability to design context-aware systems that improve AI output relevance. Experience in optimizing pipeline performance is key.
Excellent communication and collaboration skills, with enthusiasm for teamwork; effective stakeholder management experience desired.
A curious, innovative and growth mindset — motivated to explore frontier AI developments, stay updated on AI trends, and apply learnings to real-world challenges.
Bachelor's or higher degree in Computer Science, Data Science, Artificial Intelligence or similar fields or comparable demonstrated hands/on experience.
Personal and professional growth through self-leadership and continuous development.
Meaningful work that positively impacts our workplace, our customers, and society.
An open and collaborative culture that encourages cross-functional teamwork and provides networking opportunities.
A supportive and inclusive environment that promotes a balanced and sustainable work-life, with flexible working conditions when suitable for the role.
Benefits such as our share based reward program Eken, company pension plan, employee offer for banking products, health insurance.
be a part of an international team of professionals, who are jointly delivering challenging projects, maximizing customer value and increasing Swedbank’s competitive advantage”. Nanna Nenzén Filipovic, your future manager
We look forward to receiving your application by 15.06.2026.Location: Stockholm & Umeå
Recruiting manager: Nanna Nenzén Filipovic
We may begin the selection during the application period, so we welcome your application as soon as possible.
We would like to let you know that a background check and a drug test may be a part of the process for this role.
We have made our choice regarding recruitment media and therefore kindly decline contact with ad sellers or sellers of other recruitment services.
Swedbank does not discriminate anybody based on gender, age, sexual orientation or sexual identity, ethnicity, religion or disability – everybody is welcome.
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