Senior Associate, AI Enablement Lead

Position: Senior Associate - AI Enablement Lead
Location: Hybrid - Radnor, PA
Firm: ~80-person firm managing $11 billion for US non-profits
Compensation : Competitive compensation and benefits package
Culture: Mission-driven, cross-disciplinary, intellectually rigorous approach
Reports To: Head of Software Engineering

Organizational Overview
TIFF was founded in 1991 by a network of foundations and is a mission-driven, not-for-profit organization dedicated to delivering investment solutions to foundations, endowments, and other charitable institutions. Since its inception, TIFF has exclusively served the non-profit community by providing experienced manager selection and access, risk-sensitive asset allocation, and integrated member service to institutions with long-term investment horizons. TIFF provides major endowment investment capabilities to non-profits that lack the scale and in-house resources to pursue sophisticated investment strategies on their own. TIFF Advisory Services is the regulated advisory firm that administers the investment vehicles bearing the TIFF name. TIFF’s mission, credo, and board membership can be found at www.tiff.org.

Position
The Senior Associate - AI Enablement Lead is a new role within TIFF’s Technology team, created to help the firm get real value from AI. The firm’s AI capabilities are expanding quickly, but most staff are already at capacity, with little room to learn new tools or rethink how things get done. The AI Enablement Lead does two things: teaches staff to use the firm’s approved AI tools on their real day-to-day tasks, and embeds with teams to build alongside them, prototyping agents, automations, and proof-of-concept applications; most of the teaching happens through the building. The role requires recent, hands-on generative AI experience and carries no business-as-usual responsibilities; its sole focus is making AI part of how the firm operates.

Validated prototypes are handed to the engineering team to be rebuilt, secured, and supported; the Lead proves the concept, engineering institutionalizes it, and that handoff is a hard line. The role is technology-forward but is not an engineering role, and works closely with the firm’s Business Analyst to turn validated concepts into well-scoped requirements.

Key Responsibilities include, but are not limited to:

- Enablement and education

Build and run a practical enablement program that raises day-to-day AI fluency across the firm, grounded in people’s real workflows rather than generic tool demonstrations.

- Serve as the firm’s go-to resource for AI questions: how to approach a task, which tool fits, and where AI is and is not the right answer; follow the tool landscape and advise leadership on what is worth adopting, and when.

- Develop role-specific guidance, playbooks, and reusable patterns so good practice spreads without the Lead in the room, and partner with firm-wide rollout owners to drive sustained adoption.

- Prototyping and proof of concept

Work directly with teams to build agents, automations, and proof-of-concept applications that test whether an AI idea delivers real value before the firm commits engineering resources.

- Move from idea to working prototype quickly using AI-assisted and low-code tooling, with enough rigor that stakeholders can judge the concept on something real.

- Hand validated prototypes to the engineering team with clear context and requirements so they can be rebuilt, secured, and supported as production systems.

- Maintain a prioritized pipeline of AI initiatives, steer teams away from duplicated effort, and report adoption and impact metrics so the firm can see whether the investment is paying off.

- Use-case discovery

Engage with teams across investment, client service, operations, and finance to understand how work gets done and where AI can remove friction or expand capacity.

- Translate business needs into clearly scoped opportunities, separating quick wins from work that warrants real engineering investment, and work with the firm’s Business Analyst where deeper requirements work is needed.

- Responsible use and the production boundary

Reinforce the boundary between prototype and production: end users prototype to learn and validate; engineering builds what ships.

- Work within the firm’s data security, privacy, and compliance requirements, and help staff understand what data can and cannot be used with which tools.

- Partner with technology leadership to shape sensible, lightweight guardrails that protect the firm without slowing experimentation down.

Qualifications

- 5+ years’ experience in roles bridging business and technology (enablement, implementation, business analysis, technical product or program management, or consulting), including at least two years of hands-on work with generative AI tools: LLM workflows, agents, and automations.

- Bachelor’s degree in a relevant field, or equivalent practical experience.

- Demonstrated, hands-on building with modern AI tooling. Candidates should be able to walk through things they have built and, where they can, show them.

- Experience driving technology adoption, training, or change management, regardless of formal title.

- Experience in OCIO, asset management, or another regulated, data-sensitive environment is a strong plus.

- Practical fluency across the current AI tool landscape: enterprise copilots, LLM assistants, AI coding assistants, and agent-building tools, plus core concepts such as retrieval and prompt and context design.

- Able to build working prototypes independently, wiring together tools and data and shipping something useful; technical enough to build, not only advise, with a clear grasp of the security difference between a prototype and a production system in a regulated firm.

- Data literacy to work with the firm’s data responsibly. Familiarity with SQL and how data models and sources fit together helps.

- Able to explain technical ideas to non-technical colleagues, teach patiently, and build trust with stakeholders across the firm, including skeptics.

- Comfortable influencing without authority and working with people at whatever level of AI fluency they have.

- Self-directed and curious about AI: someone who follows the space, tries new tools as they appear, and forms their own view of what works.

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.

TIFF is committed to fostering a diverse, equitable, and inclusive workplace. We are an Equal Opportunity Employer. TIFF provides reasonable accommodations to qualified individuals with disabilities, in accordance with applicable law. If you need assistance or an accommodation during the application process or to perform the essential functions of the role, please contact Human Resources.