Head of Enterprise AI Applications

SiTime Corporation•Santa Clara, CA

5d•$238,950 - $341,710

About The Position

SiTime is seeking a Head of Enterprise AI Applications to define and execute the strategy for AI-powered solutions across the company. This hands-on leadership role will lead development, deployment, and scaling of AI applications that deliver measurable business outcomes across functions such as Sales, Finance, Operations, HR, and Marketing. The role is responsible for building a high-performing team, delivering production-grade solutions, and making AI a trusted, everyday capability across the organization. The position owns the AI applications vision and roadmap, designs agentic solutions to automate workflows and augment teams, and drives company-wide adoption through change management, training, and enablement. It architects full-stack AI solutions, selecting suitable LLMs and integrating them with enterprise systems and data sources; leads solutions from prototype through production; and partners with business leaders, IT, Product, Engineering, and Business Applications to deliver integrated, supportable, scalable solutions. The role also establishes evaluation, testing, and monitoring practices; manages decisions across models and AI platforms; sets up enterprise AI governance and responsible-use standards; and advises leadership on developments and investment opportunities in AI. Compensation includes base salary, a quarterly bonus tied to innovation goals, and equity grants. The listed pay range is $238,950–$341,710 USD.

Requirements

At least 5 years of experience building software or AI solutions, including at least 4 years in AI/ML and 2 years leading applied-AI teams.
Track record of building agentic AI solutions for business functions and shipping them to production at scale.
Hands-on experience with the Microsoft Copilot ecosystem, including M365 Copilot, Copilot Studio, and agent builder, to build, customize, and deploy agents.
Demonstrated success driving organizational AI adoption and enablement through change management, training, and measurable uptake.
Experience architecting full-stack AI solutions, selecting appropriate LLMs and integrating with core business systems such as CRM, ERP, and data platforms.
Deep, current understanding of LLMs and generative AI, including prompting, retrieval-augmented generation (RAG), fine-tuning, agents, and evaluation methods.
Strong engineering fundamentals and ability to engage deeply with the team on architecture, integrations, and trade-offs.
Proven ability to hire, lead, and develop high-performing technical teams and direct reports.
Excellent communication and influence skills, including explaining complex concepts to executives and end users and rallying non-technical teams around AI.
Practical understanding of responsible AI, including safety, privacy, bias, and governance.
Experience establishing enterprise AI governance frameworks, including policies, review and approval processes, and operating models.
Experience presenting AI strategy, progress, and recommendations to senior leadership and C-suite stakeholders.
Hands-on experience with agentic AI orchestration frameworks such as LangChain, Semantic Kernel, AutoGen, or similar for multi-step agent workflows.
Familiarity with AI governance and compliance frameworks such as the NIST AI Risk Management Framework or EU AI Act, applied in an enterprise context.
Demonstrated change management experience driving adoption of new technology or ways of working across a broad, cross-functional organization.
Experience managing vendor and partner relationships for AI tooling, platforms, or services, including contract evaluation and strategic alignment.

Responsibilities

Define and own the vision and roadmap for AI-powered solutions aligned with company and business-function priorities.
Design and deliver agentic AI solutions across functions such as Sales, Finance, Operations, HR, and Marketing to automate workflows and augment teams.
Drive AI adoption through change management, training, and enablement, and measure and grow adoption over time.
Architect end-to-end AI solutions, selecting appropriate LLMs and integrating them with core business systems and data sources such as CRM, ERP, ticketing systems, and knowledge bases.
Lead the design, development, evaluation, and deployment of LLM- and agent-driven applications from prototype to scaled production.
Partner with business leaders, IT, Product, and Engineering to identify high-impact opportunities and deliver value.
Collaborate with the Business Applications team to embed AI in enterprise systems and workflows, ensuring solutions are integrated, supportable, and scalable.
Establish evaluation, testing, and monitoring practices for model performance, accuracy, latency, and cost.
Make build-versus-buy decisions across foundation models, fine-tuning, RAG, agents, and orchestration, balancing capability, cost, and reliability.
Establish an enterprise AI governance framework, including policies, review processes, an operating model, and standards for evaluating, approving, and deploying AI.
Set responsible AI standards and guardrails for safety, privacy, fairness, and governance, and ensure compliance with relevant policies and regulations.
Keep the organization informed about developments in AI and advise leadership on investment opportunities.
Hire, lead, and develop high-performing AI teams and direct reports.
Present AI strategy, progress, and recommendations to senior leadership and C-suite stakeholders.
Manage vendor and partner relationships for AI tools, platforms, or services, including contract evaluation and strategic alignment.