Senior Software Engineer

Job ID: 4043 Welcome to Group Technology, where we pride ourselves on engineering solutions that directly impact Nordea's 2030 goals to modernize data technology and accelerate AI. We’re seeking a Technical AI Safety Specialist to build deep, hands-on technical expertise in the engineering-heavy risk areas that come with scaling AI and agentic systems across topics like AI gateway architecture, MCP servers and agentic tooling, red-teaming methodology, evaluation frameworks, and the cybersecurity implications of new AI capabilities. You’ll partner closely with engineering, architecture, and information security teams to turn that technical understanding into pragmatic governance guidance, technical risk assessments, and internal white papers. This role sits within the AI Safety team, which brings together architectural governance, AI risk operations and advisory capabilities to enable safe, trusted and compliant AI across Nordea. As AI and agentic systems become more complex, the team needs stronger technical expertise to understand how these systems are designed, secured, evaluated and operated, and to translate that understanding into practical guardrails, risk assessments and guidance. Nordea is a place where traditions meet tomorrow. We're not just a bank; we're a tech employer on a mission to evolve finance securely and responsibly. Together, we impact millions of people's daily lives by ensuring they can access our solutions anytime, anywhere, while safeguarding their personal data and wealth. Join us in making an impact on the banking industry.  This position is a full-time, permanent role with hybrid working location based in Helsinki, Finland, Copenhagen, Denmark, or Stockholm, Sweden. About our team  Meet the AI Safety team, part of AI Portfolio Delivery within Group AI, responsible for enabling safe, trusted and compliant AI across Nordea through efficient, scalable and holistic risk governance. AI and agentic systems are moving fast, and so is our remit. We’re building deeper technical capability so that our governance keeps pace with new architectures, tooling, and emerging risks, helping to streamline AI deployment and maintenance while ensuring effective risk management and regulatory adherence. Our culture emphasizes collaboration, continuous learning, and innovation in an open environment where diverse ideas thrive. We support each other's growth while pushing technology boundaries, prioritizing work-life balance, and open communication.  What you will be doing: Build and maintain deep technical knowledge of engineering-heavy AI risk areas, including AI gateways (e.g. Kong), MCP servers and agentic tooling, evaluation frameworks, and red-teaming methodology Partner with engineering, platform, and cybersecurity teams to understand how AI and agentic systems are built and operated, and translate that understanding into governance guidance Track emerging AI developments and assess the technical and security implications of new capabilities, protocols, and attack surfaces Author technical white papers, position papers, and risk assessments on AI infrastructure and emergent risk topics, written for both technical and non-technical audiences Contribute technical input to governance frameworks, evaluation criteria, and technical controls for AI systems, without owning their day-to-day implementation Engage with senior technical stakeholders across the organisation to pressure-test governance approaches against real engineering constraints Act as a technical peer to engineering and cybersecurity teams in cross-functional discussions on AI security protocols and technical controls Help shape what technical AI safety expertise should look like as the team’s scope and remit continue to evolve Translate deep technical understanding into governance positions, RACI, and decision processes that first- and second-line stakeholders can act on Who you are  You have a technical/engineering background and enjoy going deep on hard technical problems. You may not write production code day to day anymore, but you can hold your own in a conversation with a platform engineer about gateway architecture, or with a security engineer about red-teaming an LLM. You’re comfortable operating in ambiguity – this role and team will keep evolving as the AI landscape does – and you’re good at translating technical depth into guidance that non-technical stakeholders can act on. We're looking for someone with most of the following experience and skills: BSc or MSc in Computer Science, Software Engineering, Cybersecurity, or a related technical discipline 5+ years of experience in software engineering, platform engineering, security engineering, or a similar hands-on technical role 5+ years of experience working with AI/ML system architectures, including how models, data pipelines, and infrastructure fit together Experience with API gateways or similar infrastructure (e.g. Kong) and/or agentic protocols such as MCP Understanding of cybersecurity principles as they apply to AI and agentic systems, including common attack surfaces Familiarity with red-teaming or adversarial testing approaches for AI systems Hands-on experience with cloud platforms (e.g. AWS, GCP) in an AI context Ability to communicate technical depth clearly to both technical and non-technical stakeholders It would be ideal if you also have: Experience with AI evaluation frameworks or model/system testing methodologies Experience writing technical white papers, research summaries, or position papers Exposure to AI governance, risk, or compliance work, and an interest in bridging it with engineering Understanding of regulatory frameworks for AI in financial services or other regulated industries Experience with vendor or third-party technical risk assessments for AI platforms Familiarity with data governance and privacy considerations for AI systems We encourage applications from candidates who are passionate about the technical side of AI safety and meet most of these criteria. If this sounds like you, get in touch! Next steps We kindly ask you to submit your application as soon as possible, but no later than 16/08/2026. Any applications or CVs sent by email, direct messages, or any other channel than our application forms, will not be accepted or considered. If you have any questions about our recruitment process, please reach out to our tech recruiter and main point of contact anna.dahlstrom@nordea.com.

About the company: Navinci is a Swedish biotech company developing innovative technologies to study protein interactions in their native spatial context, with a strong legacy in in situ proximity ligation assay technology and a broad portfolio of products for spatial proteomics. About the role: We are looking for a Senior Data Scientist in image analysis to join Navinci and build scalable, automated pipelines for spatial interactomics. You will take strong ownership in designing and advancing computational methods, with a focus on creating robust, reproducible workflows that incorporate rigorous quality control and leverage deep learning to address complex biological questions. The work will support both internal R&D and external collaborations. You will be part of a highly skilled, and growing team, playing a key role in advancing pipeline development and computational innovation. The role requires both independent problem-solving and effective collaboration in a dynamic environment, helping position Navinci at the forefront of spatial biology and emerging AI technologies. Key Responsibilities Design, develop, and maintain scalable, automated analysis pipelines and reproducible workflows with robust quality control for spatial interactomics data. Develop novel computational methods and apply deep learning to address complex biological questions and enable new analysis capabilities. Build internal tools and contribute to best practices in pipeline design, reproducibility, and code quality. Collaborate with multidisciplinary teams and external partners to translate biological problems into computational solutions. Mentor and guide junior team members while contributing to a collaborative, adaptive, and high-performing team environment. Work effectively in a dynamic environment with adaptability, independence, and strong collaboration, while staying current with advances in spatial omics and AI (e.g., agentic/LLM-based workflows). Qualifications Required: PhD in Computational Biology, Bioinformatics, Computer Vision, or a related field (or equivalent industry experience). Strong understanding of spatial omics data and associated analysis challenges. Demonstrated ability to design and develop robust, reproducible computational methods and pipelines, including components such as image processing, clustering, spatial analysis, statistical analysis and data visualization. Strong proficiency in Python, with experience developing production-quality code for data analysis and pipeline development. Proven, hands-on experience in developing and applying deep learning models, using machine learning frameworks (e.g., PyTorch, Scikit-learn). Ability to independently solve complex, open-ended problems. Strong communication and collaboration skills in interdisciplinary environments. Preferred: Industry experience in image analysis methods and/or pipeline development is a strong plus. Experience with agentic workflows, AI agents, or LLM-based systems. Experience applying best practices in scientific programming and/or software engineering (e.g., testing, debugging, version control, CI/CD). Experience with GPU programming and performance optimization. Experience with high-throughput computing such as HPC or cloud computing. Experience with tool development, UI/UX, or containerization (e.g., Docker). What We Offer Opportunity to shape scientific direction in a cutting-edge company. Agile teams with fast decision-making and direct impact. Dynamic environment with growth and leadership potential. Close collaboration across R&D, product, and commercial teams. Applications will be reviewed on a rolling basis.