Sobre esta vaga de AI Platform Lead na Sensata Technologies
General Responsibilities
- Leads the design, development, testing, deployment, and maintenance of complex software. Writes code, builds reusable modules, and converts business and technical requirements into sound designs.
- Selects methods, technologies, interfaces, and design patterns for ambiguous assignments, ensuring solutions meet architecture, scalability, security, and industry standards.
- Leads code, design, and release reviews; refactors legacy code, integrates components, resolves defects, and improves application performance.
- Builds automated tests for reliability and regression coverage and advances reusable patterns, development standards, build automation, and continuous delivery.
- Leads major projects or workstreams by estimating effort, managing risks and dependencies, coordinating milestones, and partnering across functions on features and troubleshooting.
- Documents key processes and technical decisions, mentors engineers, evaluates new technologies, and supports quality, security, and industry compliance.
Experience / Qualifications
- Relevant work experience or knowledge of the role
- 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
- Takes ownership of meeting 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, build, and run Sensata's enterprise AI platform on Azure, including Azure AI Foundry, Azure OpenAI, the LLM gateway, telemetry, and shared developer tools. Implement the reference architecture defined by the Principal AI Architect.
- Stand up and manage Dev/Test/Prod environments, CI/CD pipelines, and infrastructure-as-code so AI solutions are built, tested, and released the same way every time.
- Own production readiness and operations for AI solutions, including release management, monitoring, incident response, and scaling priority use cases from pilot to production.
- Put MLOps/LLMOps practices in place for model deployment, evaluation, versioning, and performance monitoring.
- Put platform security, identity and access controls, and responsible AI guardrails in place. Partner with IT on the underlying cloud, network, and identity foundations.
- Build reusable components, templates, APIs, and automation so AI engineers and data scientists can deliver faster and more consistently.
- Provide visibility into platform usage, performance, reliability, and cost. Drive optimization and own the platform roadmap.
- Lead and develop platform engineers, set engineering standards, and coordinate delivery across global teams.
Additional Qualifications:
- 8+ years of experience in software engineering, platform engineering, cloud infrastructure, or enterprise technology roles.
- Professional proficiency in spoken and written English
- Experience building and supporting enterprise platforms, shared services, or developer enablement capabilities at scale.
- Strong knowledge of cloud platforms, APIs, platform architecture, system integration, and modern software development practices.
- Experience supporting AI, machine learning, generative AI, or advanced analytics solutions in enterprise environments.
- Knowledge of platform governance, security controls, identity and access management, monitoring, and operational excellence.
- Experience developing scalable services, automation frameworks, and reusable technical capabilities.
- Proven ability to lead complex technical initiatives and influence cross-functional teams without direct authority.
- Strong understanding of AI platform operations, usage monitoring, cost management, and performance optimization.
- Experience with Azure, AI platform technologies, MLOps, or cloud-native architectures preferred.
- Advanced degree in Computer Science, Engineering, Information Systems, or a related field preferred.
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