Global AI Solution Engineer

Posted Yesterday
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5 Locations
In-Office or Remote
Senior level
Robotics • Analytics • Energy
The Role
Develop and deliver AI-enabled solutions that translate business needs into practical applications. Build prototypes, predictive models, generative AI applications, agents, RAG workflows, APIs, and integrations using Python, SQL, Azure, and Snowflake. Evaluate solution quality, safety, cost, and reliability while supporting responsible AI, compliance, CI/CD, production readiness, monitoring, and documentation. Collaborate with analysts, engineers, architects, platform specialists, and business stakeholders in an Agile delivery environment.
Summary Generated by Built In

At ABB, we help industries run leaner and cleaner—and every person here makes that happen. You’ll be empowered to lead, supported to grow, and proud of the impact we create together. Join us and help run what runs the world.

This Position reports to:

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.

Building a cleaner, smarter future takes all kinds of minds: the curious, the courageous, and the creative. We welcome people from all backgrounds and experiences.

Ready to make an impact? Apply today or visit www.abb.com to learn more about the impact of our solutions across the globe.

Recruitment Fraud Warning

ABB never asks for payment from job applicants. All genuine job offers follow a formal application and interview process.

View current job openings and apply at: https://careers.abb/global/en/home

For more information, read our full fraud warning notice at: https://global.abb/group/en/careers/how-to-apply/fraud-warning

Skills Required

  • At least 2 years of relevant experience delivering AI, machine learning, or advanced analytics solutions, including a 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 at minimum C1 level
  • Hands-on proficiency in Python and SQL
  • 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
  • General understanding of classical machine learning concepts
  • Working experience with version control and testing, preferably GitHub or Azure DevOps
  • Experience documenting AI solutions and understanding data quality concepts
  • Experience working in an Agile or similar delivery setup
  • Ability to clarify technical, data, and AI-specific aspects of business requirements
  • Ability to explain technical options, limitations, and trade-offs and collaborate in multidisciplinary teams
  • Relevant professional certifications, such as Azure AI Engineer Associate, Azure Data Scientist Associate, Azure AI Apps and Agents Developer Associate, SnowPro Core, SnowPro GenAI, or Fabric Data Engineer Associate
  • Practical experience with Snowpark ML, Cortex AI, Cortex Search, Cortex Analyst, or Snowflake AI Functions
  • Experience with Microsoft Fabric or Power BI AI capabilities
  • Experience with Azure DevOps for work planning, execution, and reporting
  • Experience using SAP and Salesforce enterprise data as inputs to AI/ML solutions

ABB Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about ABB and has not been reviewed or approved by ABB.

  • Healthcare Strength — Healthcare coverage is described as comprehensive, with medical, dental, vision, mental health support, and disability and life insurance included. Immediate eligibility in some roles reinforces the sense of dependable core coverage.
  • Leave & Time Off Breadth — Time-off offerings are described as broad, including paid holidays, sick days, volunteer time, sabbaticals, and, in some cases, 25 days of PTO. Flexible scheduling and remote-work options add to perceived time-off and flexibility value.
  • Retirement Support — Retirement benefits are positioned as robust, including a 401(k) with company contributions or matching and, in some cases, profit sharing or pension savings. Stock purchase/share acquisition programs complement longer-term savings options.

ABB Insights

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The Company
HQ: Zürich
104,000 Employees
Year Founded: 1988

What We Do

ABB is a leading global technology company that energizes the transformation of society and industry to achieve a more productive, sustainable future. By connecting software to its electrification, robotics, automation and motion portfolio, ABB pushes the boundaries of technology to drive performance to new levels. With a history of excellence stretching back more than 130 years, ABB’s success is driven by about 110,000 talented employees in over 100 countries. www.abb.com

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