Agentic AI Data Scientist - Build Production AI Solutions

Smarte Penger; Bergen; Remote; NOK 900,000 - 1,200,000; Full time

Job summary

Equinor in Bergen is seeking a Data Scientist to work at the frontier of generative and agentic AI. You will design, develop and test AI solutions, integrate prompting strategies, retrieval systems and evaluation methods, and work with large language models and cross-functional teams to deploy impactful solutions across the organisation.

This role blends data science, AI engineering and product development, offering opportunities to experiment, learn, and contribute to intelligent systems that

Qualifications

• Masters or PhD in STEM fields or closely related discipline.
• Proven hands-on experience in data science, ML and AI deployment in production.
• Practical knowledge of modern language models and agentic AI.

Responsibilities

• Design, develop and test agentic AI solutions.
• Develop prompting strategies, retrieval systems and evaluation approaches.
• Work with large language models and multimodal AI technologies.
• Collaborate with engineers, architects and business experts.
• Contribute to production deployment of AI solutions.
• Measure and improve solution performance, quality and user adoption.
• Identify new opportunities where AI can create business value.

Skills

Masters/PhD in STEM fields

Hands-on data science experience

ML deployment in production

Python programming

Education

Masters or PhD in operations research, applied mathematics, computer science, data science, control/automation, engineering

Tools

LangGraph

MAF

CrewAI

Job description

Equinor in Bergen is seeking a Data Scientist to work at the frontier of generative and agentic AI. You will design, develop and test AI solutions, integrate prompting strategies, retrieval systems and evaluation methods, and work with large language models and cross-functional teams to deploy impactful solutions across the organisation.

This role blends data science, AI engineering and product development, offering opportunities to experiment, learn, and contribute to intelligent systems that