Global AI Solution Engineer

Technology, Data & Digital · Data, AI & Analytics · Data Science · Machine Learning · Artificial Intelligence

In short

ABB is seeking an AI Solution Engineer to develop AI-enabled solutions for industrial automation. This hybrid role in Australia involves bridging business needs with practical AI applications, working with various data specialists and leveraging platforms like Azure and Snowflake to build, validate, and deploy solutions. You will contribute to quality, compliance, and operational readiness, ensuring solutions meet business value, safety, and reliability standards.

Responsibilities

Work with Data Analysts and business stakeholders to clarify business needs, expected outcomes, success measures, AI-specific data requirements, risks, 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 Advanced Analytics Architect and platform architects.
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, including predictive models, GenAI applications, and AI agents.
Apply Snowflake AI/ML capabilities to build and validate machine learning and generative AI solutions.
Evaluate and test solutions for grounding, answer quality, model/agent behavior, business value, safety, cost, and operational reliability.
Apply Responsible AI, information security, privacy, access-control, and IT compliance requirements.
Contribute to CI/CD, production readiness, handover, and monitoring design.
Support incident and problem analysis related to AI solutions.
Document AI solutions, including their logic, assumptions, limitations, test results, and operational requirements.
Work as part of a multidisciplinary delivery team with Data Analysts, Snowflake Developers, Data Engineers, Power BI/Fabric Developers, and platform specialists.

Requirements

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).
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.
General understanding of classical machine learning concepts.
Working experience with version control and testing, preferably using GitHub or Azure DevOps.
Experience documenting AI solutions and understanding data quality concepts, with attention to data accuracy and consistency.
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.

Desired Qualifications

Experience with Microsoft Fabric or Power BI AI capabilities is an advantage.
Hands-on experience with classical machine learning is an advantage where relevant to the use case.
Exposure to CI/CD and deployment processes is an advantage.
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 certifications, Fabric 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.

Benefits

Empowered to lead
Supported to grow
Proud of the impact we create together

Skills

PythonSQLGenerative AIRAGEmbeddingsVector SearchPrompt EngineeringContext EngineeringEvaluationAzure AI FoundryAzure Machine LearningSnowflake CortexSnowflake IntelligenceMachine LearningGitHubAzure DevOpsCI/CDSAPSalesforceSnowpark MLCortex AICortex SearchAI FunctionsMicrosoft FabricPower BI

#AI#Machine Learning#Data Science#GenAI#Cloud

About ABB

We are a technology leader in electrification and automation, enabling a more sustainable and resource-efficient future.

ABB is a technology leader in electrification and automation, enabling a more sustainable and resource-efficient future. The company’s solutions connect engineering know-how and software to optimize how things are manufactured, moved, powered and operated. Building on more than 130 years of excellence, ABB’s ~105,000 employees are committed to driving innovations that accelerate industrial transformation. www.abb.com\nPrivacy notice & house rules: https://social.abb/social-media-information\n\nBefore applying for a job at ABB , please read our Fraud Warning:…

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