Global AI Solution Engineer

ABB Inc

Rotterdam

Hybrid

EUR 70,000 - 110,000

Full time

14 days+

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Job summary

ABB zoekt een AI Solution Engineer die AI-gedreven oplossingen vertaalt naar praktische toepassingen binnen de Automation IS-teams. Je werkt aan AI-componenten, evaluatie en productie-compatibiliteit met data uit SAP en Salesforce.

Je beheert ontwikkeling met Python/SQL, bouwt Azure/Snowflake-gebaseerde AI-diensten en levert meetbare bedrijfswaarde. Een hybride werkmodel en samenwerking met Data Analysts en engineers staan centraal.

Qualifications

  • Minstens 2 jaar ervaring met AI/ML-oplossingen
  • 4–6 jaar ervaring in Data Science, AI/ML Engineering, BI analytics of soortgelijke data-rollen
  • Master of gelijkwaardige technische opleiding
  • Vloeiend Engels (minimum C1)

Responsibilities

  • Verduidelijken van bedrijfsbehoeften, uitkomsten en AI-gegevensvereisten
  • Beoordelen of AI/analytics/automatisering of een conventionele oplossing de behoeften het beste adresseren
  • Oplossingen ontwerpen op basis van goedgekeurde patronen en guidance van architecten

Skills

Python
SQL
AI/ML engineering
Data analytics
RAG/embeddings
Cloud platforms
Git/CI-CD
English fluency

Education

Master's degree (technical)

Tools

Azure AI Foundry
Azure Machine Learning
Snowflake Cortex
Power BI
Microsoft Fabric

Job description

Bij ABB helpen we industrieën beter te presteren - slanker en schoner. Vooruitgang is hier een verwachting - voor jou, je team en de wereld. Als wereldwijde marktleider geven we je wat je nodig hebt om dat waar te maken. Het zal niet altijd gemakkelijk zijn, groeien vergt lef. Maar bij ABB sta je er nooit alleen voor. Doe wat de wereld doet draaien.

Deze functie rapporteert aan:

Senior Operation Manager for D&A

Mission of the Role

Are you passionate about turning business needs into practical, AI-enabled solutions and excited to be part of a global company transforming industry with cutting-edge technology? ABB is looking for an AI Solution Engineer to join our Automation IS team.

In this role, you will bridge the gap between business needs and practical AI-enabled solutions. You will assess whether AI is the right approach and recommend an implementation approach based on the standards, reference architectures and technology guidance defined by the Advanced Analytics Architect and relevant platform architects. You will stay hands-on throughout delivery, working with Data Analysts, Snowflake Developers, Power BI/Fabric Developers, Data Engineers and other specialists to build, validate and hand over working solutions. You will also contribute to project set-up, incremental delivery, solution quality, production readiness and reuse across Automation.

Work model: #LI Hybrid Area: This role contributes to AU IS in AU.

Responsibilities
Business understanding and solution fit
  • Work with Data Analysts and business stakeholders to clarify:business needs and expected outcomessuccess measuresAI-specific data and context requirementsrisks and ownership
  • Assess whether AI, analytics, automation or a conventional solution best addresses the identified business need.
  • Recommend solutions based on approved patterns and guidance from the Advanced Analytics Architect and the Snowflake, Azure and Fabric platform architects.
Build and development
  • Develop and validate AI components, proofs of concept, prototypes and minimum viable solutions using Python, SQL and approved technologies.
  • Build Azure- or Snowflake-based AI applications and services, including orchestration, retrieval, RAG, agent logic, APIs, evaluation and integration components.
  • Create implementation assets, including prompts, agent instructions, evaluation datasets, notebooks, application logic, automated workflows, tests and deployment assets.
  • Use enterprise data from SAP and Salesforce to develop AI/ML solutions that address business needs and deliver measurable business value. These include predictive models, GenAI applications and AI agents.
  • Apply Snowflake AI/ML capabilities to build and validate machine learning and generative AI solutions using enterprise data. These include Snowpark ML, Cortex AI, Cortex Search and AI Functions.
Quality, compliance and operations
  • Evaluate and test solutions for grounding, answer quality, model or agent behaviour, business value, safety, cost and operational reliability.
  • Apply the defined Responsible AI, information security, privacy, access-control and IT compliance requirements within the assigned solution scope. Work with architecture, platform, security and operations specialists where required.
  • Contribute to CI/CD, production readiness, handover and monitoring design.
  • Support incident and problem analysis related to AI solutions within the assigned scope.
  • Document AI solutions, including their logic, assumptions, limitations, test results and operational requirements.
Collaboration
  • Work as part of a multidisciplinary delivery team with Data Analysts, Snowflake Developers, Data Engineers, Power BI/Fabric Developers and platform specialists.
Requirements (Mandatory)
Experience and education
  • At least 2 years of relevant experience delivering AI, ML or advanced analytics solutions, including at least one solution taken from requirements through implementation.
  • 4–6 years of professional experience in Data Science, AI/ML Engineering, BI analytics or a similar data-focused role.
  • Master's degree in a technical discipline or equivalent practical experience.
  • Fluent spoken and written English (minimum C1 level).
Technical skills
  • Hands-on proficiency in Python and SQL for data preparation, API integration, testing and solution development.
  • Strong practical understanding of generative AI application patterns, including RAG, embeddings, vector search, prompt/context engineering and evaluation.
  • Practical experience with at least one enterprise AI development platform, preferably Azure AI Foundry, Azure Machine Learning, Snowflake Cortex or Snowflake Intelligence. Experience with Microsoft Fabric or Power BI AI capabilities is an advantage.
  • General understanding of classical machine learning concepts. Hands-on experience is an advantage where relevant to the use case.
  • Working experience with version control and testing, preferably using GitHub or Azure DevOps. Exposure to CI/CD and deployment processes is an advantage.
  • Experience documenting AI solutions and understanding data quality concepts, with attention to data accuracy and consistency.
Ways of working
  • Experience working in an Agile or similar delivery setup.
  • Ability to take part in stakeholder discussions and clarify technical, data and AI-specific aspects of documented business requirements.
  • Ability to explain technical options, limitations and trade-offs, and to work effectively in a multidisciplinary delivery team.
  • Demonstrated ability to collaborate with analysts and customers and convert documented requirements into practical AI solution components.
Nice to Have / Differentiators
  • Relevant professional certifications, particularly:Azure AI Engineer Associate (AI-102)Azure Data Scientist Associate (DP-100)Azure AI Apps and Agents Developer Associate (AI-103)SnowPro Core or GenAI certificationsFabric Data Engineer Associate (DP-700)
  • Practical experience with Snowflake AI/ML capabilities such as Snowpark ML, Cortex AI, Cortex Search, Cortex Analyst or AI Functions.
  • Experience with Azure DevOps for work planning, execution and reporting.
  • Experience using SAP and Salesforce enterprise data as inputs to AI/ML solutions.
More About Us

ABB provides a comprehensive range of integrated automation, electrical and digital systems and services for customers in the process, hybrid and maritime industries. These offerings, coupled with deep domain knowledge in each end market, help to optimize productivity, energy efficiency, sustainability and safety of industrial processes and operations.

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