Senior Insights Architect - Analytics and AI

Intuitive•Sunnyvale, CA

About The 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 techniques as 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 analytics and AI solutions.

Requirements

10+ years of hands-on experience developing analytics solutions using Snowflake, Tableau, BOXI or similar tools using Engineering data.
Hands-on experience with BOXI is a strong plus.
Demonstrated experience building, collaborating in the deployment, and maintaining ML models and/or GenAI applications in a production environment.
Experience collaborating with team working on large language models (LLMs) and prompt engineering, including integration of LLM APIs (OpenAI, Azure OpenAI, etc.) into data products.
Functional understanding and data flows of Engineering systems and processes.
Effectively communicate technical concepts — including AI model outputs and limitations — to non-technical audiences to foster understanding, influence, and build consensus across teams.
A very good team player with demonstrated ability to manage and influence without direct authority.
Strong understanding of data warehousing, data modeling, and visualization techniques.
Profound SQL knowledge and experience, including writing complex queries and optimization.
Experience leading the technical design and development of complex data products.
Previous experience integrating advanced analytics and AI solutions into business processes.
Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Information Technology, or a related field.

Nice To Haves

Strong statistical background and analytical skills.
Experience working with a leading Manufacturing organization in a regulated environment.
Experience with natural language processing (NLP) and computer vision applications.
Familiarity with AI governance frameworks and responsible AI principles.

Responsibilities

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.