Jobs at Sensata Xirgo

Supports enterprise transformation initiatives through financial forecasting, modeling, variance analysis, operational metrics, governance, executive reporting, dashboards, and KPI tracking. Partners with leaders to improve financial and operational performance, manage transformation portfolios, identify risks and opportunities, and translate data into actionable recommendations. The role also drives process improvements, accountability, value realization, and decision support across strategic initiatives.

Leads supplier quality management, problem-solving, containment, corrective actions, audits, supplier qualification, capacity verification, and process improvement. Partners with sourcing and cross-functional teams on new product development, change management, supplier performance, quality reviews, and strategic supply-chain initiatives.

Owns product strategy, roadmaps, requirements, business cases, pricing, and lifecycle management for data center power conversion and peak power solutions. The role translates hyperscaler and AI infrastructure needs into differentiated products involving 800 VDC architectures, energy storage, power conversion, protection, and distribution. Responsibilities include customer and ecosystem engagement, competitive analysis, cross-functional execution, commercialization, operational issue resolution, and identifying partnership or acquisition opportunities.

Responsible for purchasing and sourcing activities, including filling purchase orders, organizing requisitions, maintaining supplier information, monitoring orders and deliveries, forecasting item-level sales, analyzing inventory trends, and generating purchasing reports. The role collaborates with supply chain and internal teams to maintain appropriate inventory levels and improve purchasing monitoring systems.

Develops and improves manufacturing processes for electromechanical products, including process validation, equipment specifications, production launch, yield improvement, cost reduction, and design for manufacturability. Collaborates with engineering, quality, suppliers, contract manufacturers, and global production sites. Supports assembly, calibration, testing, tooling, automation, advanced quality planning, process controls, and sustained production improvements.

Coordinates projects from initiation through completion, managing schedules, budgets, scope, resources, risks, testing, documentation, training, and status reporting. Works with clients and cross-functional teams to clarify requirements, track progress, control changes, analyze performance, and escalate issues. The role requires strong organization, communication, collaboration, accountability, and proficiency with Microsoft Office tools.

Leads operations research and data science initiatives across supply chain, procurement, and engineering. Develops optimization, forecasting, statistical, and machine learning models for inventory, scheduling, capacity planning, demand, cost, and vendor analytics. Establishes modeling, validation, backtesting, monitoring, and retraining standards; partners with business leaders to drive adoption; and mentors data scientists and AI engineers.

Owns enterprise AI architecture strategy, standards, governance, and multi-year roadmaps. Designs scalable AI ecosystems across data pipelines, models, agents, platforms, integrations, security, observability, and lifecycle management. Leads Azure AI reference architecture, CI/CD, infrastructure-as-code, LLMOps/MLOps, responsible AI controls, architecture reviews, and build-versus-buy decisions. Guides multiple teams, mentors technical leaders, and translates business priorities into secure, production-ready AI solutions across enterprise functions.

Owns AI products for operations, initially focused on supply chain and expanding to procurement, quality, and engineering. Responsibilities include workflow discovery, product requirements, roadmap and backlog prioritization, pilot execution, governance, business-case development, adoption, and realized-value measurement. Partners with operations teams, AI engineers, data scientists, finance, IT, vendors, and senior leadership to move AI solutions from concept through production.

Designs, builds, deploys, and maintains production AI applications, models, services, and pipelines for supply chain use cases. Develops intelligent agents, copilots, and RAG solutions integrated with enterprise systems and data. Establishes testing, evaluation, monitoring, deployment, and release practices while improving performance, reliability, cost, and explainability. Partners with technical teams and vendors, contributes to architecture and engineering standards, communicates trade-offs, and mentors engineers.

Leads commercial data science initiatives using machine learning, forecasting, optimization, and predictive modeling to improve pricing, sales, customer prioritization, revenue forecasting, and commercial decision-making. Translates business questions into data science solutions, validates and monitors models, partners with AI and platform teams on production deployment, evaluates third-party analytics solutions, and communicates insights to executives and business stakeholders.

Owns Sensata’s commercial AI product portfolio across sales, revenue operations, pricing, marketing, and finance. Maps workflows, identifies pain points, defines product requirements, prioritizes roadmaps, and manages backlogs. Leads pilots through production, user adoption, governance, vendor integration, and value measurement. Builds business cases, tracks revenue and productivity outcomes, and communicates product decisions to senior leaders while partnering with AI engineers, data scientists, IT, Finance, and business stakeholders.

Designs, builds, and operates Sensata’s Azure AI platform and production machine learning infrastructure. Responsibilities include developing reusable platform components, CI/CD pipelines, infrastructure-as-code, MLOps and LLMOps workflows, model monitoring, observability, security controls, incident response, and developer tooling. The role requires strong Python, Azure, container, automation, and production systems experience, with a focus on reliability, scalability, responsible AI, and cost optimization.

Drive profitable growth within assigned strategic accounts in Taiwan by developing and executing account strategies, building executive relationships, identifying new business opportunities, coordinating cross-functional teams, maintaining forecasting in SFDC, and ensuring customer satisfaction and commercial excellence.

Leads the development and operation of Sensata’s enterprise AI platform on Azure, including shared AI services, infrastructure, CI/CD, MLOps/LLMOps, security controls, monitoring, and reusable developer tools. Owns production readiness, platform governance, reliability, cost optimization, and roadmap execution while leading platform engineers and coordinating delivery across global teams.

Coordinates projects from initiation through completion, managing scope, schedules, budgets, resources, risks, testing, documentation, training, and stakeholder communication. The role defines project objectives, tracks progress and performance, manages client and supplier relationships, presents status updates, escalates issues, and ensures timely, on-budget delivery.

Builds and operates production AI applications for commercial teams. Responsibilities include developing generative AI, agent, machine learning, and RAG solutions; integrating AI with Salesforce, CRM, ERP, pricing, and quoting systems; creating data pipelines and reliable APIs; monitoring model quality, bias, drift, and performance; defining evaluation and release criteria; applying security controls; supporting production solutions; and mentoring engineers.

Builds and deploys production AI solutions for supply chain, procurement, quality, and engineering operations. Develops agents, copilots, RAG solutions, model-driven tools, pipelines, and MLOps/LLMOps workflows integrated with ERP, planning, EDI, and manufacturing systems. Partners with technical and business teams to define use cases, evaluate models, monitor performance, drive adoption, and improve reliability, cost, latency, and explainability. Mentors engineers and contributes to architecture and technical standards.

Designs, develops, deploys, and operates production AI solutions across commercial, engineering, quality, operations, supply chain, and procurement functions. Builds generative AI, agent, copilot, RAG, machine learning, and computer vision applications; integrates them with enterprise systems; and creates data pipelines, MLOps workflows, reusable frameworks, and monitoring practices. Owns solutions from prototype through production, applies security controls, evaluates performance and business impact, collaborates with stakeholders and vendors, and mentors engineers.

Designs and validates mechanical products that meet customer requirements, creating drawings and documentation for internal release. Leads mechanical design activities on new product development teams, supports prototypes, production validation, and product launches, and collaborates with customers, manufacturing, quality, suppliers, and global engineering teams. Applies expertise in materials, manufacturing processes, GD&T, tolerance analysis, design for manufacturing, corrosion, welding, and mechanical engineering fundamentals.