Job description

The Expert AI Architect serves as the enterprise AI architecture authority, defining standards, frameworks, and best practices for scalable, secure, and responsible AI solutions. This role drives architectural consistency across AI platforms, agents, models, integrations, and governance while guiding technical direction across engineering, IT, cybersecurity, and business teams. General Responsibilities Own and evolve the enterprise AI architecture vision and multi-year roadmap, setting direction for platforms, tools, frameworks, integration patterns, and reusable standards across diverse business and technology environments. Lead the translation of highly complex, ambiguous business priorities into scalable AI architectures that shape enterprise technology and data strategy while meeting security, privacy, regulatory, and compliance requirements. Architect and provide authoritative direction for end-to-end AI ecosystems spanning data pipelines, model development, deployment, observability, evaluation, lifecycle management, and integration with critical enterprise platforms. Establish enterprise-wide architectural principles, governance frameworks, and decision criteria for generative AI, machine learning, large language models, retrieval-augmented generation, intelligent agents, APIs, and model integration, resolving the most complex or novel design challenges. Influence enterprise priorities and investment decisions by building alignment among engineering, data science, product, cybersecurity, legal, compliance, and senior business stakeholders on responsible, resilient, and value-driven AI solutions. Set technical direction and guide multiple teams through implementation, validation, governance, operational readiness, and cost optimization for business-critical production AI systems. Anticipate industry and technology shifts; assess emerging AI capabilities, vendors, and frameworks; and define adoption strategies that balance innovation, enterprise risk, scalability, interoperability, and long-term sustainability. Serve as the enterprise authority and escalation point for AI architecture, providing expert consultation, design review, and mentorship to senior engineers, architects, data scientists, and technical leaders across the organization. Experience / Qualifications A university degree required (i.e. Bachelors degree) or equivalent relevant work experience. Must be a team player able to work in a fast-paced environment with demonstrated ability to handle multiple competing tasks and demands Strong communication skills; oral, written and presentation Strong organization, planning and time management skills to achieve results Strong personal and professional ethical values and integrity Holds self-accountable to achieving goals and standards Proficient in Microsoft Office programs (Outlook, Word, PowerPoint, and Excel) Strong interpersonal & collaboration skills to work effectively with all levels of the organization including suppliers and/or external customers Additional Responsibilities : Own the enterprise AI reference architecture and platform blueprint on Azure, covering agents, RAG, model services, the LLM gateway, identity, observability, and cost controls. Define the patterns for Dev/Test/Prod environments, CI/CD, and infrastructure-as-code across AI solutions, and guide the AI Platform Lead in implementing them. Build reference implementations, templates, and reusable components hands-on to prove out patterns and speed up delivery by AI engineers and data scientists. Serve as design authority for internal and third-party AI solutions, leading architecture reviews and build/buy/reuse decisions. Set standards for model selection, evaluation, LLMOps/MLOps, security guardrails, and production readiness. Own the AI platform architecture and standards, partnering with IT on the underlying cloud, network, and identity foundations. Design how priority AI use cases across supply chain, commercial, quality, and engineering connect to core enterprise systems so they scale from pilot to production. Additional Qualifications : 12 years of experience in software engineering, data, AI engineering, or enterprise architecture, including recent hands-on delivery of generative AI solutions. Proven record of shipping GenAI/LLM solutions (agents, RAG, copilots) into production at enterprise scale. Deep expertise in Azure, including Azure AI Foundry, Azure OpenAI, Entra ID, and API management. Strong hands-on experience with CI/CD, infrastructure-as-code (e.g., Bicep, Terraform), and LLMOps/MLOps practices. Experience establishing architecture standards, design reviews, and reusable patterns adopted across multiple teams. Solid understanding of AI security, data governance, privacy, and responsible AI controls. Ability to influence senior business and technical leaders and turn business priorities into practical architecture decisions. Experience in manufacturing, industrial, or supply chain environments preferred. Advanced degree and/or Azure, architecture, or AI certifications preferred #LI-JL1 Base Salary Range: $181,600.00 - $249,700.00 At Sensata, our employees are the key to our success and growth. We recognize that each individual brings their own unique experience, therefore the base salary range information shown above is a general guideline only. Sensata considers several factors when extending an offer, including, but not limited to, a candidate’s experience and qualifications, as well as internal equity, market and business considerations. In addition to base salary, Sensata offers competitive medical, dental, vision, life and disability insurance plans, along with education reimbursement, wellness programs, a 401(k) retirement plan with Company matching, and a variety of paid time off, such as vacation or flex-time, sick, bereavement, and parental leave. Certain positions are also eligible for short-term incentive and long-term incentive programs. Smarter Together Collaborating at Sensata means working with some of the world’s most talented people in an enriching environment that is constantly pushing towards the next best thing Employees work across functions, countries and cultures gaining new perspectives through mutual respect and open communication As OneSensata , we are working together to make things work together Click here to view Sensata Recruitment Privacy Statement Click here to view our Sensata Recruitment Privacy Statement for China NOTE: If you are a current Sensata employee (or one of our Affiliates), please back out of this application and log into Workday via the Company Intranet to apply directly. Type FIND JOBS in the Workday search bar.

Requirements

Must-haves

General Responsibilities
Set technical direction and guide multiple teams through implementation, validation, governance, operational readiness, and cost optimization for business-critical production AI systems.
Experience / Qualifications
A university degree required (i.e. Bachelors degree) or equivalent relevant work experience.
Must be a team player able to work in a fast-paced environment with demonstrated ability to handle multiple competing tasks and demands
Strong communication skills; oral, written and presentation
Strong organization, planning and time management skills to achieve results
Strong personal and professional ethical values and integrity
Holds self-accountable to achieving goals and standards
Proficient in Microsoft Office programs (Outlook, Word, PowerPoint, and Excel)
Strong interpersonal & collaboration skills to work effectively with all levels of the organization including suppliers and/or external customers
Own the enterprise AI reference architecture and platform blueprint on Azure, covering agents, RAG, model services, the LLM gateway, identity, observability, and cost controls.
Define the patterns for Dev/Test/Prod environments, CI/CD, and infrastructure-as-code across AI solutions, and guide the AI Platform Lead in implementing them.
Build reference implementations, templates, and reusable components hands-on to prove out patterns and speed up delivery by AI engineers and data scientists.
Serve as design authority for internal and third-party AI solutions, leading architecture reviews and build/buy/reuse decisions.
Set standards for model selection, evaluation, LLMOps/MLOps, security guardrails, and production readiness.
Own the AI platform architecture and standards, partnering with IT on the underlying cloud, network, and identity foundations.
Design how priority AI use cases across supply chain, commercial, quality, and engineering connect to core enterprise systems so they scale from pilot to production.
12 years of experience in software engineering, data, AI engineering, or enterprise architecture, including recent hands-on delivery of generative AI solutions.
Proven record of shipping GenAI/LLM solutions (agents, RAG, copilots) into production at enterprise scale.
Deep expertise in Azure, including Azure AI Foundry, Azure OpenAI, Entra ID, and API management.
Strong hands-on experience with CI/CD, infrastructure-as-code (e.g., Bicep, Terraform), and LLMOps/MLOps practices.

Nice-to-haves

Experience in manufacturing, industrial, or supply chain environments preferred.
Advanced degree and/or Azure, architecture, or AI certifications preferred

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningazurellmci/cdapi

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Parental Leave

Wellness