Senior Insights Architect - Analytics and AI

Intuitive; Sunnyvale (CA); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Intuitive seeks an experienced Senior Insights Architect to lead analytics and AI solution design and integration within Engineering processes. You will shape data product architectures, evaluate AI approaches, and guide cross-functional teams to deliver scalable, secure analytics solutions.

In this senior role, you will drive the roadmap for analytics and AI initiatives, collaborating with data engineers, data scientists, ML engineers, and product engineers to ensure successful deployment and

Qualifications

• Strong background in designing analytics and data product architectures.
• Experience evaluating AI/ML approaches for engineering or business problems.
• Ability to translate business needs into scalable technical requirements.

Responsibilities

• Translate analytics needs into scalable technical solutions for AI-driven insights and automation.
• Lead design and development of analytics data products including predictive models and GenAI tools.
• Evaluate AI/ML approaches to solve Engineering business problems.
• Manage analytics product roadmap aligned with Engineering objectives.
• Collaborate with data engineers, data scientists, ML engineers, and product engineers.
• Ensure data quality, security, and governance, including responsible AI practices.
• Influence stakeholders and champion AI tool adoption across Engineering.
• Stay current with data, analytics, and AI trends relevant to Engineering management.

Skills

Analytics architecture

AI/ML concepts

Data modeling

Stakeholder management

Data warehousing

Tools

Python

SQL

ETL pipelines

GenAI tools

ML frameworks

Job description

Job Description

Primary Function of Position

We are seeking an experienced Senior Insights Architect for Analytics and AI Solutions to lead the design and implementation of our advanced analytics, data product architecture and collaborate during development of AI solutions, while also playing a key role in integrating these capabilities into our business processes. The ideal candidate will have a strong background in developing analytics, evaluating AI solutions using Engineering and Supply Chain Data,hands-on experience collaborating during building and deploying AI/ML models and GenAI-powered solutions,and experience leading the technical design and development of complex data products. They will have a deep understanding of data warehousing, data modeling, and visualization techniquesas well as modern AI frameworks and large language model (LLM) integration patterns and will be able to effectively translate business requirements into scalable and performant technical solution requirements. This role requires a strong ability to influence and collaborate across teams, even without direct authority, to ensure successful implementation and adoption of analyticsand AIsolutions.

Essential Job Duties

• Work closely with business stakeholders across Process, Design and Supplier Engineering functions to understand their analytics needs and translate them into scalable and performant technical solutions, including requirements for AI-driven insights and automation opportunities.
• Lead the design and development of complex analytics and data products that address Engineering challenges and opportunities, including predictive models, anomaly detection systems, and GenAI-powered tools, and drive their integration into key Engineering processes in partnership with process owners.
• Evaluate, prototype, and recommend AI/ML approaches (supervised, unsupervised, and generative) to solve Engineering business problems.
• Manage the roadmap for analytics and data products, including AI/ML initiatives, aligning with Engineering strategic objectives, while effectively balancing competing requirements in a dynamic Engineering environment.
• Collaborate with data engineers, data scientists, ML engineers, and product engineers to ensure seamless integration and deployment of analytics and AI solutions.
• Ensure data quality, security, and governance across all analytics solutions, including responsible AI practices such as model explainability, bias detection, and compliance.
• Build strong relationships and influence stakeholders across the organization, particularly within Engineering functions, to gain buy-in and support for analytics and AI initiatives, and champion the adoption of AI tools and platforms to improve team productivity and decision-making.
• Stay up to date on the latest technologies and trends in data, analytics, and artificial intelligence, particularly as they relate to Engineering management.