Senior Applied Artificial Intelligence AI Engineer - Sensata Technologies

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 :

Rapidly design, build, and deploy AI solutions, delivering usable prototypes and production-ready applications

Develop end-to-end AI/LLM workflows (RAG, summarization, classification, agents) including APIs, data pipelines, and system integrations

Build scalable solutions using Python, REST APIs, Azure OpenAI/OpenAI, vector databases, and orchestration frameworks

Ingest, process, and work directly with messy, unstructured enterprise data (e.g., PDFs, Excel, SharePoint)

Create user-facing tools and applications with appropriate interfaces, integrations, and deployment mechanisms

Implement and manage evaluation, monitoring, and reliability frameworks (testing, scoring, human-in-the-loop, logging, error analysis)

Evaluate, benchmark, and support due diligence of vendor solutions against internal builds

Prioritize and deliver AI initiatives based on business value, scalability, and speed-to-impact across multiple enterprise use cases

Operate effectively in ambiguous environments with evolving requ