Semantic data modelling and data governance specialists — multiple tracks

Build the semantic and governance foundation that agentic AI depends on — so agents reason from shared enterprise meaning and act on data that is safe to act on.

Relevant experience & expertise

• Demonstrable hands-on production experience in one of the following specialisations: Semantic Data Modelling, AI-Ready Data Product Ownership, or Governed-by-Design Data Management (see more below)

• A strong understanding of how AI agents consume data, and the crucial role of robust data governance and semantics.

• Ability to translate complex technical concepts effectively between business, data, and AI stakeholders.

• Fluency in English.

Highly valued attributes

• Deep experience in data governance, data management, or enterprise semantics.

• Demonstrated ability to bridge technical AI requirements with business objectives and data capabilities.

• A pragmatic approach to governance, focusing on enablement rather than obstruction.

• Experience within industrial, energy, or other highly regulated sectors.

• Familiarity with modern data architecture principles and data product management.

• Working knowledge of Norwegian or another Scandinavian language.

About the roles

Build the semantic and governance foundation that agentic AI depends on — so agents reason from shared enterprise meaning and act on data that is safe to act on. These roles sit at the data and semantic foundation layer of the AI operating model — providing the meaning, lineage, and governance contracts that every agent and pod consumes.

• Enterprise meaning, the data catalogue, or data-management practice — depending on your track.

• Governance that AI pods and architecture treat as an enabler, not a blocker.

• Machine-readable classification, lineage, and usage terms that agents can actually consume.

• Data readiness as a real gating criterion for use-case prioritisation.

• Lineage and quality metadata surfaced in a form that supports uncertainty attribution — when agents act on low-confidence outputs, provenance must be traceable, auditable, correctable.

Why these roles exist

Aker BP is building the foundation for agentic AI at scale. We are doing this as one operating model; strategy, architecture, science, data, safety, and delivery designed to work together, not as separate teams. This role is part of that build.

We are moving AI into the core of industrial operations, work that spans physical assets, regulated environments, and decisions that affect production, safety, and the broader energy system. We work cross-disciplinarily, with a focus on shipping into production rather than running experiments indefinitely.

One role – several tracks

Apply for different tracks

We assess against a shared senior profile and match track based on strengths. Indicate a preferred track or stay open to placement.

Track 1: Enterprise semantic modeller

Own enterprise meaning as a first-class, machine-usable asset. Ensure that AI agents, analytics, and humans reason using a single coherent understanding of the business. Partner closely with domain experts to capture, maintain, and evolve enterprise semantics. Your expertise and decisions are essential for scaling meaning throughout the business.

Must-have experience

• Hands-on production work with semantic web technologies (RDF, OWL, SPARQL) or property-graph equivalents.

• Demonstrated experience capturing enterprise meaning across domains with domain experts — not just consulting frameworks.

• Working understanding of how AI agents consume semantic data and where breakdowns happen.

Preferred qualifications

• Experience with business-glossary programmes or enterprise ontology rollouts.

• Background in industrial, energy, or asset-heavy domains (oil and gas, manufacturing, utilities).

• Knowledge of OSDU, CIM, or similar industrial information models.

Track 2: AI-ready data product owner

Own the data catalogue and ensure data products are correctly defined, governed, and maintained in Purview. Provide trusted, well-structured data as the foundation for scalable AI and agent solutions. Bridge between data producers and AI consumers.

Must-have experience

• Hands-on production experience with Microsoft Purview, Collibra, Alation, or equivalent.

• Demonstrated work defining data products, data contracts, and consumer-facing data documentation.

• Working understanding of AI consumption patterns and where governance gaps cause failures.

Preferred qualifications

• Product management background applied to data assets.

• Industrial, energy, or asset-heavy domain experience.

• Familiarity with data-mesh patterns or distributed data ownership models.

Track 3: Data management lead — governed-by-design

Make data management a first-class enabler of safe, autonomous AI: gatekeeping use-case prioritisation based on data readiness, ensuring classification and usage terms are machine-readable, building traceability into agent-data interactions, and managing data quality throughout the data lifecycle. Not a compliance-watchdog role — an enabler of trustworthy autonomy with explicit attention to how data completeness and quality directly affect model confidence and downstream risk in agentic workflows.

Must-have experience

• Hands-on production work on data classification, lineage, and lifecycle in regulated environments.

• Demonstrated work translating regulatory requirements (EU AI Act, GDPR Art. 10, NIS2) into operational data-management practice.

• Working knowledge of how AI agents consume data and what data-side guardrails they require.

Preferred qualifications

• Data contracts and data-product thinking applied at enterprise scale. Microsoft Purview hands-on experience.

• Background in industrial, energy, or asset-heavy domains (oil and gas, manufacturing, utilities).

• Knowledge of OSDU or similar industrial information models.

What we offer

• Professional development
  We are committed to providing you with varied experience and enhancing your expertise, helping you build a strong CV for the future.

• Competitive compensation
  We offer a competitive salary, an opportunity to earn bonuses, a share savings programme, and a solid pension scheme.

• Work-life balance
  We value good health and work-life balance, offering good cafeterias, work-out facilities, and flexibility in working hours and location.

• Employee well-being
  We ensure you get support from our company health service and insurance programmes should anything happen.

• Diverse & inclusive environment
  We are convinced diversity is important for success, and everyone should feel involved, included, and respected.

• Accessible workplace
  Our offices are designed to be universally accessible for all.

Our culture & vision

• SAFER values
  Our foundation is built on being Seekers, Accountable, Foreseeable, Engaged, and Respectful in everything we do.

• AI-first mindset
  We are an AI-first company, committed to leading our industry in AI adoption and unlocking its transformative power.

• ONETEAM culture
  Cooperation is at our core; working with us means being part of our collaborative 'ONETEAM' culture.

• Safety priority
  We put safety first in all operations and expect the same commitment from every team member.

Application process

Background checks will be performed, following consent from relevant candidates. We ask that you enclose your diploma/grade transcript with your application. Furthermore, an assessment of affiliation to high-risk countries is carried out as part of the recruitment process for all positions in Aker BP.

Our ambition is clear: to become the world’s first AI‑native exploration and production company.

We're hiring to accelerate our journey towards becoming the first AI-native E&P company.

We didn't discover AI last year. For a decade, we've been building the data foundation and interoperable ecosystem that now lets us scale AI across some of the most complex operations in our industry. 

Our ambition is simple to state and hard to deliver: a 3x productivity improvement. Getting there demands more than incremental gains,  it requires a fundamental redesign of how work gets done. You get there by redesigning how decisions are made, how work is planned, and how assets are run, with AI agents as native participants in the operating model. And that's why we're looking for ambitious, driven AI professionals who want to help rewrite how a large industrial company operates.

If that sounds like your kind of problem, we'd like to meet you.

Aker BP uses AI-assisted review as part of the recruitment process. AI is used to structure and summarise information – all decisions are made by people.