Manager AI

Robert Half•San Ramon, CA

About The Position

Robert Half is seeking a Manager AI to provide strategic leadership for developing, delivering, and advancing the organization’s artificial intelligence capabilities, data science practices, and intelligent software solutions. The role leads multidisciplinary teams of Data Scientists, AI Engineers, Machine Learning Engineers, and related technical professionals to build scalable, secure, governed AI solutions that support critical business capabilities. The Manager AI translates enterprise AI strategy into team objectives, operating models, delivery roadmaps, and organizational capabilities that accelerate adoption and create measurable business value. The role establishes the enterprise AI technology vision, strategic architecture, and innovation roadmap, and provides leadership for architecture governance, AI-enabled applications, platform services, and reusable engineering components. It partners with executive, product, engineering, architecture, data, security, infrastructure, governance, and business stakeholders to align AI initiatives with enterprise strategy, responsible AI principles, regulatory requirements, cybersecurity, data governance, and operational excellence. The Manager AI owns AI initiative execution and delivery, manages the AI project and product portfolio, and oversees the solution lifecycle from discovery and experimentation through deployment, monitoring, optimization, and continuous improvement. The role also develops a high-performing AI organization through hiring, workforce planning, talent development, performance management, coaching, and career growth. The typical annual salary range is $123,000–$190,000, negotiable based on experience and location, and the position is eligible for a discretionary annual bonus.

Requirements

Bachelor’s degree in a related field or equivalent experience.
3+ years of professional experience in software engineering, data science, machine learning, artificial intelligence, technology delivery, and technical leadership within large-scale enterprise environments.
Demonstrated success building high-performing technical teams, delivering enterprise AI capabilities, managing complex technology initiatives, and translating business objectives into scalable AI solutions.
Experience leading AI, data science, software engineering, or technology teams responsible for developing and deploying production-grade AI capabilities.
Experience managing technical roadmaps, resource planning, delivery execution, and organizational transformation initiatives.
Track record leading complex, ambiguous technology initiatives by aligning people, processes, technical capabilities, and business priorities to deliver measurable outcomes and long-term value.
Ability to lead and develop multidisciplinary teams of Data Scientists, AI Engineers, Machine Learning Engineers, and software professionals, fostering innovation, collaboration, technical excellence, and continuous improvement.
Exceptional communication skills for explaining AI concepts, technical strategies, delivery plans, risks, and opportunities to executive, business, technical, and non-technical audiences.
Ability to partner with executives, product and engineering leaders, architects, data organizations, security and governance teams, and business stakeholders to align priorities and drive AI adoption.
Strong strategic thinking, organizational leadership, analytical problem-solving, decision-making, and execution skills in evolving AI and technology environments.
Strong technical understanding of enterprise AI, including LLMs, foundation models, generative AI applications, agentic AI, RAG, machine learning systems, AI evaluation methodologies, and emerging technologies.
Strong understanding of enterprise AI solution lifecycles, including discovery, experimentation, data preparation, model development, evaluation, deployment, monitoring, optimization, and continuous improvement.
Experience implementing or supporting responsible AI practices, including AI governance, model risk management, security, privacy, compliance, ethical AI principles, and operational controls.
Ability to evaluate emerging AI technologies, identify business opportunities, assess technical feasibility, and guide adoption decisions aligned with organizational priorities.
Experience managing AI technology roadmaps, prioritizing investments, identifying delivery risks, and partnering with technical leaders to evolve enterprise AI capabilities.
Ability to develop executive-level communication materials, AI capability roadmaps, delivery plans, operating models, investment proposals, and technical strategy documentation.
Ability to advance organizational AI maturity through team development, process improvements, technical enablement, innovation initiatives, and AI engineering best practices.

Responsibilities

Translate enterprise AI strategy into actionable team objectives, delivery priorities, operating models, and investment plans.
Guide adoption of LLMs, RAG, agentic AI, machine learning, multimodal AI, knowledge architectures, and emerging AI technologies.
Evaluate AI trends, technologies, and industry practices to inform roadmap decisions and identify innovation opportunities.
Provide strategic guidance to Data Scientists, AI Engineers, Machine Learning Engineers, and technical leaders.
Improve AI development practices across experimentation, model development, evaluation, deployment, monitoring, governance, and lifecycle management.
Establish the enterprise AI technology vision, strategic architecture, and innovation roadmap for AI platforms, intelligent systems, and enterprise engineering capabilities.
Provide technical leadership for AI architecture governance, including scalability, security, resilience, interoperability, responsible AI, regulatory compliance, and operational excellence.
Lead development and enhancement of complex AI-enabled applications, platform services, and enterprise frameworks.
Design and implement reusable, scalable components that help development teams accelerate AI solution delivery.
Promote software engineering best practices, code quality standards, and automation across AI initiatives.
Partner with executive leadership, product and engineering leaders, enterprise architects, data organizations, security, infrastructure, governance teams, and business stakeholders to shape AI strategy and accelerate transformation.
Ensure AI initiatives align with enterprise architecture, cybersecurity, responsible AI principles, regulatory requirements, data governance standards, and operational excellence objectives.
Own AI initiative execution and delivery by setting priorities, managing resources, removing barriers, and ensuring delivery of scalable, secure, impactful solutions.
Manage the AI project and product portfolio, balancing strategic investments, business priorities, dependencies, commitments, and organizational capacity.
Partner with Product Managers and other stakeholders to define requirements, establish success metrics, measure outcomes, and ensure business value.
Oversee AI solution lifecycle management from discovery and experimentation through model development, evaluation, deployment, monitoring, optimization, and continuous improvement.
Support the evolution of AI platforms, developer capabilities, data products, experimentation environments, and reusable AI services.
Lead, manage, and develop a team of AI and data science professionals.
Build and maintain a high-performing AI organization through hiring, workforce planning, talent development, performance management, and career growth strategies.
Coach and mentor technical professionals, providing career guidance, growth opportunities, feedback, and support for developing AI engineering and data science capabilities.
Establish AI governance practices for responsible, secure, reliable, and compliant AI development and deployment.
Partner with engineering, security, data governance, risk, and compliance teams to align AI solutions with enterprise standards.
Define team quality expectations and operational practices for model evaluation, validation, monitoring, performance measurement, and production readiness.
Improve AI processes, tools, methodologies, and organizational practices to increase delivery velocity, quality, and business impact.

Benefits

Group health insurance benefits, including medical, vision, and dental coverage.
Flexible Spending Account (FSA) and Health Savings Account (HSA) healthcare accounts.
Life and accident insurance.
Adoption and fertility assistance.
Paid parental leave of up to 6 weeks.
Short- and long-term disability coverage.
Paid time off for vacation, personal needs, and sick time; new hires earn up to 17 days of Choice Time Off per calendar year, prorated based on hours worked and varying by years of service.
Up to 11 paid holidays per calendar year.
401(k) savings and investment plan or deferred compensation plan if eligible.
Employer match of 100% on the first 3% of eligible employees’ contributions.
Discretionary annual bonus.