Senior IT Pillar Specialist

Job Overview

The AI/ML Developer for Engineering IT is responsible for designing, integrating, deploying, and supporting AI/ML solutions that enhance engineering applications, enterprise platforms, and digital workflows. This role focuses on translating business and engineering requirements into scalable, secure, and production-ready AI capabilities, while enabling responsible AI adoption, operational reliability, and continuous improvement across Engineering IT systems.

Key Tasks and Responsibilities

• Support the deployment, integration, and lifecycle management of AI/ML solutions within Engineering IT platforms, engineering applications, and enterprise workflows
• Collaborate with engineering application owners, business stakeholders, infrastructure teams, and vendors to identify, design, and implement AI-enabled use cases that improve engineering productivity, quality, and operational efficiency
• Develop and maintain production-ready pipelines for model deployment, monitoring, retraining, and version control, following MLOps and DevOps best practices
• Ensure secure, scalable, and reliable integration of AI/ML services with enterprise systems, databases, APIs, and cloud or on-premises environments
• Establish processes for model performance monitoring, drift detection, incident resolution, and continuous improvement to ensure stable business operations
• Work closely with data, cybersecurity, architecture, and compliance teams to ensure responsible AI adoption, data governance, privacy, and adherence to enterprise standards
• Prepare technical documentation, support materials, and knowledge transfer artifacts for Engineering IT teams, end users, and support personnel
• Provide application support and troubleshooting for AI/ML-enabled engineering solutions, including issue analysis, root cause identification, and coordination of fixes with relevant teams
• Contribute to evaluation of emerging AI tools, frameworks, and engineering technology platforms to recommend practical solutions aligned with Engineering IT strategy
• Participate in cross-functional projects, pilot programs, and digital transformation initiatives to drive adoption of AI capabilities across engineering and project delivery functions

Essential Qualifications and Education

• 2–5 years of hands-on experience in AI/ML development, deployment, or integration, with exposure to production environments
• Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, Data Science, Mathematics, or a related discipline
• Strong programming capability in Python, with practical knowledge of machine learning libraries and frameworks
• Solid understanding of machine learning concepts, model development lifecycle, model evaluation, and performance tuning
• Experience integrating AI/ML solutions with enterprise or engineering applications using APIs, services, and system interfaces
• Working knowledge of MLOps and DevOps practices, including version control, CI/CD, model deployment, monitoring, and retraining workflows
• Familiarity with cloud and on-premises deployment environments, containerization, and scalable solution architecture
• Understanding of data pipelines, data quality, and governance requirements for enterprise AI implementations
• Awareness of AI security, privacy, compliance, and responsible AI practices in enterprise settings
• Strong analytical, problem-solving, documentation, and communication skills, with the ability to collaborate effectively across business, engineering, and IT teams
• Exposure to engineering systems (2D/3D applications provided by AVEVA, HEXAGON, Bentley, Autodesk, others) digital engineering platforms, or enterprise application support will be an added advantage

#LI-NS1

#DICE