SR AI TRANSFORMATION ENGINEER
TE Connectivity Ltd.
Una candidatura completa in un minuto
Curriculum e lettera di presentazione personalizzati, pronti da inviare.
Descrizione del lavoro
TE Connectivity Ltd. is seeking an AI Transformation Engineer - Engineering Data Automation to deliver AI-enabled engineering solutions using data, simulation, CAD/CAE, and automation.
The role requires coordinating across AI, digital teams, and engineering SMEs to implement initiatives from assessment to deployment. The ideal candidate has a degree in engineering/computer science and hands-on experience with Python scripting, engineering workflows, and applying AI to engineering problems.
Competenze
- Bachelor's degree in engineering, computer science, or related discipline.
- Hands-on experience with CAD/CAE/simulation, PLM, engineering data management, or digital engineering workflows.
- Proficient in Python scripting and engineering workflow automation.
- Experience applying AI, automation, or digital tech to engineering or business problems; familiarity with generative AI/LLMs/AI agents is a plus.
- Assess system interfaces, APIs, data access, integration dependencies, and constraints.
- Familiarity with engineering data structures and digital workflows.
- Strong analytical and problem-solving skills.
Mansioni
- Identify opportunities to leverage AI within engineering data, simulation, CAD/CAE, design automation, and technical workflows.
- Evaluate data availability, quality, integration requirements, and automation opportunities.
- Collaborate with AI specialists, digital teams, and SMEs to define solution approaches.
- Define technical requirements and deployment strategies for AI initiatives.
- Develop prototypes and proofs-of-concepts to validate feasibility.
- Lead deployment of AI-enabled engineering solutions involving data integration and workflow automation.
- Coordinate with AI Hub, DDT, external resources, and technical specialists.
- Develop and deploy AI agents and engineering productivity tools.
- Drive validation, testing, and deployment activities.
- Promote adoption of AI-enabled engineering methods.
- Identify opportunities to improve engineering efficiency through automation and reusable solutions.
- Coach engineering teams on practical AI applications within workflows.
Conoscenze
Formazione
Strumenti
Descrizione del lavoro
At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world.
The AI Transformation Engineer - Engineering Data Automation is responsible for delivering AI-enabled engineering solutions that leverage engineering data, simulation, CAD/CAE environments, automation, and advanced digital capabilities. The role focuses on high-complexity initiatives requiring structured engineering data, workflow integration, automation, or technical coordination across multiple systems. This position leads the technical implementation of assigned AI initiatives from assessment through pilot, validation, deployment, and adoption.
- Identify opportunities to leverage AI within engineering data, simulation, CAD/CAE, design automation, and technical workflows.
- Evaluate data availability, data quality, integration requirements, and automation opportunities.
- Collaborate with AI specialists, digital teams, and engineering subject matter experts to define solution approaches.
- Define technical requirements and deployment strategies for approved initiatives. AI Solution Development and Deployment
- Develop prototypes and technical proof-of-concepts to validate solution feasibility before committing significant development resources.
- Lead deployment of AI-enabled engineering solutions involving data integration, workflow automation, and technical systems.
- Coordinate with AI Hub, DDT, external development resources, and technical specialists as required.
- Development and deployment of AI agents, workflow automation solutions, and engineering productivity tools.
- Drive validation, testing, and deployment activities. Engineering Automation Enablement
- Promote adoption of AI-enabled engineering methods.
- Identify opportunities to improve engineering efficiency through automation and reusable solutions.
- Coach engineering teams on practical AI applications within engineering workflows.
- Support development of scalable approaches that may be leveraged across multiple engineering teams. Experience Qualifications
- Bachelor's degree in Engineering, Computer Science, or related discipline.
- Hands-on experience with one or more engineering technology domains such as CAD, CAE/simulation, PLM, engineering data management, or digital engineering workflows.
- Demonstrated hands-on experience with Python scripting and engineering workflow automation.
- Practical experience applying AI, automation, or digital technologies to engineering or business problems; experience with generative AI, LLMs, AI agents, or workflow automation preferred.
- Assess system interfaces, APIs, data access, integration dependencies, and technical constraints.
- Familiarity with engineering data structures and digital engineering workflows.
- Strong analytical and problem-solving skills.
- Passion for AI-enabled engineering transformation
- Bachelor's degree in Engineering, Computer Science, or related discipline.
- Hands-on experience with one or more engineering technology domains such as CAD, CAE/simulation, PLM, engineering data management, or digital engineering workflows.
- Demonstrated hands-on experience with Python scripting and engineering workflow automation.
- Practical experience applying AI, automation, or digital technologies to engineering or business problems; experience with generative AI, LLMs, AI agents, or workflow automation preferred.
- Assess system interfaces, APIs, data access, integration dependencies, and technical constraints.
- Familiarity with engineering data structures and digital engineering workflows.
- Strong analytical and problem-solving skills.
- Passion for AI-enabled engineering transformation.
Generally requires Bachelors degree in appropriate field with a minimum of 5 years of progressively responsible professional level experience; Masters degree or higher or local equivalent may be preferred at this level
SET : Strategy, Execution, Talent (for managers)
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