AI Engineering Manager

Shape is seeking a Lead AI Engineering Manager to drive data and artificial intelligence strategy, building the platforms and teams that power next-generation industrial solutions.

This pivotal leadership role will bring technical vision and expertise, guiding the development and deployment of scalable, secure, and innovative data and AI products aligned with business goals and product vision.

The successful candidate will lead talented multidisciplinary teams including data engineers, machine learning engineers, AI specialists, and platform architects, fostering a culture of technical excellence, collaboration, and continuous learning.

Working closely with key stakeholders across business and product, you will translate needs into cutting-edge solutions that deliver measurable business value.

Responsibilities:

• Define and execute overall data and AI strategy directly supporting the companys industrial product vision and roadmap.
• Architect and oversee end-to-end development of data and AI platforms ensuring scalability, security, and modularity.
• Lead, mentor, and retain high-performing teams promoting a culture of innovation, ownership, and technical rigor.
• Implement and enforce best practices for data governance, quality, privacy, compliance, and responsible AI aligned with industry regulations.
• Cultivate strategic partnerships evaluate third-party technologies and lead platform evolution integrating latest advances in AI/ML cloud and data engineering.
• Champion a data-driven mindset empowering all functions to leverage AI for informed decision-making.
• Establish and track KPIs to measure the business impact of data and AI solutions.

Requirements:

• Bachelors or higher degree in Computer Science Engineering Mathematics Statistics or a related STEM field.
• Solid experience in technical leadership of end-to-end data AI and ML projects including managing multidisciplinary engineering teams.
• Proven hands-on expertise in Python software engineering cloud platforms AWS Azure GCP data architecture and scalable data pipelines.
• Deep familiarity with AI/ML frameworks and tools Scikit-Learn TensorFlow PyTorch HuggingFace etc. MLOps best practices and platform development.
• Track record in building robust internal platforms APIs and data/ML products with a focus on quality security and reliability.
• Experience implementing governance privacy and compliance standards with a strong commitment to ethical and explainable AI.
• Strategic planning project portfolio management and the ability to influence both technical and non-technical audiences.
• Excellent communication and stakeholder management skills.

Differentiators:

• Technical Expertise: Experience with Edge AI/IoT solutions relevant for industry knowledge graphs and ontologies computer vision and predictive maintenance or advanced time series analysis.
• Business Relevance: Background in industrial or B2B data-driven products.
• Innovation: Participation in open innovation patenting or contributions to the data/AI community.
• Change Management: Leading organizational AI/analytics adoption in complex environments.

Benefits:

• PPR (Profit Sharing): Extra compensation based on the companys results according to your performance.
• Health and Dental Plan: Care and well-being ensured.
• Flexible Benefit: Amount used according to your needs food transportation education culture and health.
• Flexible Hours: Work at the best time for you and have a better quality of life.
• Massages and Manicure in the Office: Relaxation and self-care encouraged.
• Mentorship Program: Development opportunities with experienced professionals.
• Gympass: Health and wellness supported.
• Snacks in the Office: Enjoy snacks at work.
• Inclusive Environment: Diversity valued and respected.
• Day off in Your Birthday Month: Celebrate in any way you prefer.
• Extended Maternity/Paternity Leave: Important time with family supported.
• Childcare Assistance: Support for young children.
• Continuous Individualized Development Support: Personalized support for professional growth.
• Culture and Well-being: Mental health work-life balance and cultural connection fostered.