Global AI Solution Engineer

ABB is hiring a Global AI Solution Engineer in Bengaluru, India. Level rates it ; you can apply on ABB.

Level's read on this job

Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
The posting mentions RAG, AI agents and AI safety among its tools and skills.
Level classes it as a mid-level role.
ABB has 2,100+ other open roles on Level.
Posted in the last few days.

AI in this role

ragai-agentsai-safety

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

How we rate this

Global AI Solution Engineer at ABB rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Global AI Solution Engineer is an open job at ABB.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Bangalore, Karnataka, India.
The job was posted on October 27, 2026.
Seniority: mid.
Applications are handled by ABB. Apply on ABB

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI agentsAI Safety

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How do you decide when an AI agent can act on its own versus asking for approval first?
How do you think about the risk of an AI system in this kind of role failing silently?
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: RAG, AI agents, and AI Safety. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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