AI and Machine-Learning Engineers

Join our AI team to design, build, and productionise cutting-edge ML, AI, and agentic AI solutions, driving innovation across various specialisations from agent engineering to AI systems integration and product development.

Must haves

• Strong software engineering fundamentals: you write production code, not just notebooks; apply version control, code review, and reproducibility standards to all ML or AI development work.

• Experience building and shipping ML or AI-powered systems, ideally including LLM-based applications or ML solutions in production systems.

• Comfort with evaluation-driven development and production observability.

• Collaborative instincts: you will work daily with domain experts, platform engineers, and architects.

• Pragmatism about when to build custom versus reuse platform capabilities.

Nice to have

• Mentorship and team development, raising the bar for those around you.

• Ability to communicate complex probabilistic concepts to non-technical stakeholders.

• Recognized research contributions (e.g., publications, open source projects, invited talks).

• Background in industrial, energy, or similarly consequential domains.

• Proficiency in Norwegian or other Scandinavian languages.

About the roles

We are hiring engineers across several tracks to build, integrate, and productionise AI and agentic AI solutions within our cross-functional delivery pods. All roles share a common core – building production-grade AI systems – but differ in specialisation.

In this role, you will be responsible for:

• Build and ship production AI and agentic AI features within a cross-functional pod.

• Design, evaluate, and harden agent workflows, APIs, and AI-powered integrations depending on your track.

• Partner with domain experts, architects, and platform engineers to reuse central capabilities where possible.

• Apply evaluation-driven development and production observability as part of every release, CI/CD practices, and automated testing.

• Design and implement uncertainty-aware agent workflows: explicit confidence thresholds, graceful degradation paths, and human escalation triggers for agent actions where model reliability is insufficient for unassisted execution.

• Contribute to the reusable pattern catalogue and raise the bar for engineering quality across pods.

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 specialisations

Apply for different tracks.

We encourage you to apply with a preferred specialisation and an openness to discuss adjacent tracks. We assess core engineering strength first, and match specialisation based on pod needs and candidate strengths. We assess against a shared senior profile and match track based on strengths. Indicate a preferred track or stay open to placement. Available specialisations include: Track A – Agent Engineer / LLM Engineer, Track B – AI Systems / Integration Engineer, and Track C – AI Product Engineer.

Track A: Agent Engineer / LLM Engineer

Design, build, and productionise AI agents that reason, orchestrate tools, and integrate with enterprise platforms. Focus on agentic patterns (ReAct, plan-execute, critic-actor), multi-agent coordination, guardrails, and evaluation. Significant emphasis on automating the data product lifecycle through agents.

Must-have

• Experience with agent frameworks, tool-use design, prompt-injection defenses, and RAG architectures. - Calibrated uncertainty estimation for agent decision points.

Nice-to-have

• Experience with multi-agent coordination patterns (planner-executor, critic-actor, etc.). - Proven ability to develop and deploy LLM applications with a strong focus on robustness, uncertainty, and performance. - Contributions to open-source LLM projects or relevant research publications.

Track B: AI Systems / Integration Engineer

Design and build production-grade AI systems including agent orchestration, APIs, and integration with enterprise platforms. Focus on reliability, scalability, and secure execution of AI workflows across our ecosystem (CDF, Fabric, ADME/OSDU, Integration Platform).

Must-have

• Strong API design background, including RESTful and GraphQL. - Extensive experience with event-driven architectures (e.g., Kafka, Azure Service Bus). - Proficiency in enterprise integration patterns and data orchestration within large-scale systems.

Nice-to-have

• Experience with cloud platforms (Azure, AWS) and containerisation (Docker, Kubernetes). - Knowledge of data governance and security best practices for AI systems. - Understanding of MLOps principles for seamless integration and deployment.

Track C: AI Product Engineer

Operate at the intersection of domain, AI, and engineering. Design, prototype, and implement AI solutions; iterate rapidly with users; ensure solutions are practical, scalable, and aligned with evaluation and platform standards. Strong user empathy and prototyping chops matter most here.

Must-have

• Demonstrated strong product sense with a focus on user needs and business value. - Experience with UX collaboration, rapid prototyping, and conducting user research. - Ability to translate complex AI capabilities into intuitive product features.

Nice-to-have

• Experience bringing AI-powered products from concept to market. - Proficiency in A/B testing and quantitative analysis for product iteration. - Deep understanding of specific industrial domains, e.g., energy, manufacturing, or logistics.

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.