Job description

The Senior AI Engineer, Commercial builds and runs the AI applications that help Sensata's commercial organization (Sales, Marketing, Revenue Operations, and Commercial Finance) grow revenue, win and keep customers, and understand performance against peers. Working closely with the Lead Data Scientist, Commercial, and business stakeholders, the role turns models and generative AI into production tools supporting day-to-day commercial workflows. General Responsibilities Design, develop, and deploy production models, services, and pipelines that are reliable, scalable, and maintainable. Partner with data science, product, data engineering, and platform teams to translate business problems into technical solutions. Build and optimize model training, evaluation, deployment, monitoring, and retraining workflows. Improve model performance, latency, cost efficiency, reliability, and explainability in production environments. Develop reusable infrastructure, tooling, libraries, and patterns that accelerate team delivery. Monitor deployed models for performance degradation, bias, drift, and operational issues; recommend and implement corrective actions. Collaborate with stakeholders to communicate technical trade-offs, risks, timelines, and recommendations clearly. Mentor engineers and contribute to technical standards, best practices, and architecture decisions. Stay current with advances in practices. 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 : Lead the development and deployment of enterprise AI applications from concept through production. Build and deploy generative AI and agent solutions for commercial use cases, such as lead and opportunity triage and routing, account insights, next-best-offer, and competitor and peer performance intelligence. Integrate AI into commercial systems (Salesforce, CRM, ERP, pricing, and quoting) so insights show up where sellers and leaders already work. Build data pipelines that combine internal commercial data with external sources such as earnings calls, financial filings, and market and news data. Put data science models (scoring, propensity, forecasting) into production as reliable services and APIs. Define evaluation and release criteria, including accuracy and source-grounding checks for executive-facing outputs, plus adoption and business-impact metrics. Own solutions end to end, from prototype through production support, and iterate directly with commercial users. Apply security and access controls suited to customer, pricing, and financial data. Partner with platform, IT, and vendors (including Salesforce) to meet technical, security, and operational requirements. Additional Qualifications : 5 years of software engineering experience delivering production applications, including 2 years building AI, machine learning, generative AI, or intelligent automation solutions. Strong proficiency in Python, SQL, APIs, system integration, cloud technologies, and modern software development practices. Hands-on experience with large language models (LLMs), intelligent agents, copilots, and retrieval-augmented generation (RAG), including evaluating and monitoring output quality. Knowledge of software testing, CI/CD, deployment automation, and production support best practices. Experience integrating solutions with enterprise platforms, business applications, and data ecosystems; Salesforce or other CRM experience strongly preferred. Experience working with sales, marketing, or commercial finance stakeholders, with a working understanding of concepts such as pipeline, bookings, pricing, and margin. Azure, Azure AI services, Copilot Studio, Power Platform, or Databricks experience preferred. Advanced degree in Computer Science, Software Engineering, Artificial Intelligence, or a related technical field preferred. #LI-SK1 Base Salary Range: $115,620.00 - $158,983.00 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
Design, develop, and deploy production models, services, and pipelines that are reliable, scalable, and maintainable.
Partner with data science, product, data engineering, and platform teams to translate business problems into technical solutions.
Build and optimize model training, evaluation, deployment, monitoring, and retraining workflows.
Improve model performance, latency, cost efficiency, reliability, and explainability in production environments.
Develop reusable infrastructure, tooling, libraries, and patterns that accelerate team delivery.
Monitor deployed models for performance degradation, bias, drift, and operational issues; recommend and implement corrective actions.
Collaborate with stakeholders to communicate technical trade-offs, risks, timelines, and recommendations clearly.
Mentor engineers and contribute to technical standards, best practices, and architecture decisions.
Stay current with advances in practices.
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
Lead the development and deployment of enterprise AI applications from concept through production.
Build and deploy generative AI and agent solutions for commercial use cases, such as lead and opportunity triage and routing, account insights, next-best-offer, and competitor and peer performance intelligence.

Nice-to-haves

Experience integrating solutions with enterprise platforms, business applications, and data ecosystems; Salesforce or other CRM experience strongly preferred.
Azure, Azure AI services, Copilot Studio, Power Platform, or Databricks experience preferred.
Advanced degree in Computer Science, Software Engineering, Artificial Intelligence, or a related technical field preferred.

Application prep

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Keywords to mirror

aimachine learningpythonsqlci/cdazure

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Parental Leave

Wellness