NXP Semiconductors
NXP is seeking a GenAI DevOps Program Manager that will oversee the strategy, development and deployment of generative AI (GenAI) technologies, ensuring they are integrated efficiently and securely into the development and operations (DevOps) lifecycle. This role combines high‑level program management with deep technical knowledge of both DevOps principles and AI/ML, focusing on innovation, efficiency, and responsible AI practices.
Location:
Austin, TX (Hybrid; 3 days in office, 2 days work from home each week)
Roles and responsibilities
Strategic leadership:
Develop a comprehensive vision for GenAI adoption within DevOps workflows, aligning initiatives with broader organizational goals.
Program coordination:
Manage large‑scale GenAI initiatives through the full lifecycle, from hypothesis validation and fine‑tuning to deployment and post‑release evaluation.
Cross‑functional collaboration:
Act as a bridge between AI research, engineering, and product teams to facilitate communication and ensure alignment.
Risk management:
Identify potential risks associated with GenAI development, such as model accuracy, bias, and security vulnerabilities, and develop mitigation strategies.
Process definition:
Establish and improve the processes used by GenAI teams to coordinate, communicate, and resolve cross‑team issues.
Education and change management:
Foster a GenAI‑forward culture by providing education and training to development and operations teams.
Performance tracking:
Define and track key performance indicators (KPIs) for GenAI adoption and measure the business impact and ROI of initiatives.
Vendor management:
Manage relationships with external vendors providing AI training and tools.
Automation:
Drive the infusion of GenAI into CI/CD pipelines to automate tasks like code generation, testing, and monitoring.
Required skills and qualifications Technical expertise
Generative AI:
Knowledge of AI/ML concepts, including large language models (LLMs), prompt engineering, model training, and fine‑tuning.
DevOps:
Deep understanding of DevOps practices, such as continuous integration (CI), continuous delivery (CD), infrastructure as code (IaC), and site reliability engineering (SRE).
Cloud computing:
Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and associated tools for managing infrastructure and AI workloads.
Strategic planning:
Ability to create roadmaps, prioritize projects, and align initiatives with business goals.
Agile methodology:
Experience with Agile and Scrum to manage the fast‑paced development of AI products.
Risk management:
Capacity to identify project risks and develop contingency plans.
Communication:
Exceptional written and verbal communication to effectively engage both technical and non‑technical stakeholders.
Leadership:
Strong collaborative leadership and influencing skills to drive alignment and motivate cross‑functional teams.
Problem‑solving:
A proactive, problem‑solving mindset and the ability to operate effectively in ambiguous, fast‑paced environments.
Experience and education
12+ years
in program or project management, preferably in AI/ML or technology‑driven environments.
Proven track record
of delivering complex, cross‑functional programs.
Education:
Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, or related field.
Seniority level:
Director
Employment type:
Full‑time
Job function:
Project Management and Strategy/Planning
Industries:
Semiconductor Manufacturing
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Location:
Austin, TX (Hybrid; 3 days in office, 2 days work from home each week)
Roles and responsibilities
Strategic leadership:
Develop a comprehensive vision for GenAI adoption within DevOps workflows, aligning initiatives with broader organizational goals.
Program coordination:
Manage large‑scale GenAI initiatives through the full lifecycle, from hypothesis validation and fine‑tuning to deployment and post‑release evaluation.
Cross‑functional collaboration:
Act as a bridge between AI research, engineering, and product teams to facilitate communication and ensure alignment.
Risk management:
Identify potential risks associated with GenAI development, such as model accuracy, bias, and security vulnerabilities, and develop mitigation strategies.
Process definition:
Establish and improve the processes used by GenAI teams to coordinate, communicate, and resolve cross‑team issues.
Education and change management:
Foster a GenAI‑forward culture by providing education and training to development and operations teams.
Performance tracking:
Define and track key performance indicators (KPIs) for GenAI adoption and measure the business impact and ROI of initiatives.
Vendor management:
Manage relationships with external vendors providing AI training and tools.
Automation:
Drive the infusion of GenAI into CI/CD pipelines to automate tasks like code generation, testing, and monitoring.
Required skills and qualifications Technical expertise
Generative AI:
Knowledge of AI/ML concepts, including large language models (LLMs), prompt engineering, model training, and fine‑tuning.
DevOps:
Deep understanding of DevOps practices, such as continuous integration (CI), continuous delivery (CD), infrastructure as code (IaC), and site reliability engineering (SRE).
Cloud computing:
Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and associated tools for managing infrastructure and AI workloads.
Strategic planning:
Ability to create roadmaps, prioritize projects, and align initiatives with business goals.
Agile methodology:
Experience with Agile and Scrum to manage the fast‑paced development of AI products.
Risk management:
Capacity to identify project risks and develop contingency plans.
Communication:
Exceptional written and verbal communication to effectively engage both technical and non‑technical stakeholders.
Leadership:
Strong collaborative leadership and influencing skills to drive alignment and motivate cross‑functional teams.
Problem‑solving:
A proactive, problem‑solving mindset and the ability to operate effectively in ambiguous, fast‑paced environments.
Experience and education
12+ years
in program or project management, preferably in AI/ML or technology‑driven environments.
Proven track record
of delivering complex, cross‑functional programs.
Education:
Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, or related field.
Seniority level:
Director
Employment type:
Full‑time
Job function:
Project Management and Strategy/Planning
Industries:
Semiconductor Manufacturing
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