Expert Agentic Business Engineer
Technology, Data & Digital · Data, AI & Analytics · Data Science · Machine Learning · Software Engineering
In short
Responsibilities
- Own delivery from idea to production: frame business problems, shape agentic AI solution designs, prototype quickly, and industrialize into production-ready services with measurable outcomes.
- Build agentic AI applications: design and implement agents that can reason, plan, use tools, and interact with enterprise systems (e.g., advisor tooling, analytics platforms, internal APIs).
- Partner with stakeholders end-to-end: collaborate with Private Banking/AWM business leaders, architects, engineers, and control functions to ensure solutions deliver real value and can be adopted at scale.
- Engineer for governance and safety: implement evaluation strategies, guardrails, and human-in-the-loop patterns suitable for regulated banking environments (privacy, auditability, model risk expectations).
- Enable reuse and scale: build reusable patterns, components, and reference implementations to accelerate delivery across a portfolio of use cases.
- Operate and improve: monitor agent behavior in production, iterate on prompts/tools/logic based on evals and feedback, and continuously improve quality, cost, latency, and safety.
Requirements
- Hands-on agentic AI experience, including designing and building agent workflows (planner–executor, tool calling, multi-agent, human-in-the-loop).
- Strong LLM ops and evaluation mindset: quality/correctness, latency, cost, and safety; ability to define test sets and run disciplined experimentation.
- Guardrails and Responsible AI experience: input/output validation, prompt safety, data leakage prevention, and controls appropriate for regulated environments.
- Strong software engineering skills with Python (modular design, testing, version control) and comfort working in notebook-based experimentation.
- Cloud and integration experience: deploying AI services in AWS, integrating via REST APIs, and familiarity with containerisation/Kubernetes and CI/CD.
- Data/analytics platform experience (e.g., Snowflake) for grounding, retrieval, and context management.
- Business engineering strength: ability to translate stakeholder needs into solution requirements, KPIs, and adoption plans; strong communication and collaboration skills.
Desired Qualifications
- Curious, innovative team player with a can-do attitude, always looking for ways on how we can unlock the next level for our customers.
- Curious, outcome-driven and pragmatic senior data scientist who can take ownership, influence stakeholders, and raise modelling and engineering standards while delivering working solutions at pace.
Benefits
- You will join a team building practical, high-impact AI capabilities across AWM – working on real advisor and operational workflows, with strong visibility and a clear focus on measurable outcomes.
- You will help shape how we build, govern, and scale agentic AI in a Nordic, regulated banking context.
- As one of the biggest employers in the Nordics, Poland and Estonia, you have excellent opportunities to evolve, develop and move forward with us.
Skills
We are a universal bank with a 200-year history of supporting and growing the Nordic economies – enabling dreams and aspirations for a greater good. Every day, we work to support our customers’ financial development, delivering best-in-class omnichannel customer experiences and driving sustainable change. We are a full-service universal bank and the third largest corporation in the Nordic region and one of the top 10 financial services companies in Europe based on market capitalisation. We are present in 17 countries, including our four Nordic home markets which together constitute the 10th…
Company
NordeaJob Posted
2 weeks ago
Expires
in 3 days
Employment Type
Full Time
Work mode
On Site
Experience Level
Senior
Locations
København S, Denmark
Stockholm, Sweden
Applicants
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