<p><strong>Position: Director, AI Operations</strong></p> <p><strong>Reporting to: VP, Real World Data (RWD) Solutions</strong></p> <p><strong>Location: Philadelphia, PA or Remote</strong></p> <p><br><br></p> <p><strong>How you will help</strong></p> <p>As a forward-deployed AI operator within Real-World Data Solutions (RWDS), you will work at the intersection of people, process, data, and technology to turn messy operational challenges into AI-enabled systems that perform in daily work.</p> <p>You will embed directly with the teams doing the work: observing how workflows actually operate, identifying the right intervention, building the smallest useful solution, testing it with real users, and improving it until it delivers measurable value. Sometimes that solution will use AI; sometimes deterministic automation, an existing platform, or a process redesign will be the better answer. Your job is to make that judgment and own the outcome.</p> <p>This is a player-coach role. You’ll lead a small team of AI solutions specialists while staying hands-on in the build. You should be comfortable building with modern AI, automation, analytics, and low-code tools, while partnering with data and engineering teams when a solution requires production-grade infrastructure.</p> <p>Examples of problems you might tackle include:</p> <ul> <li>Reducing the time required to translate a life-sciences research question into a feasible patient cohort</li> <li>Turning fragmented presale and delivery workflows into connected, AI-assisted processes</li> <li>Helping analysts find and apply complex data source-specific knowledge more consistently</li> <li>Automating repetitive workflow steps while preserving appropriate human review</li> <li>Creating tools that make expert RWD methodologies more accessible and reusable across teams</li> </ul> <p>Because this role sits at the center of how RWDS delivers for clients, the work you do here should show up in two core ways: how clients experience working with us, and how profitably we operate.</p> <p> </p> <p><strong>What you will do</strong></p> <p><strong>Build</strong></p> <ul> <li>Discover and document how work actually happens: the people, approvals, exceptions, and informal tools (spreadsheets, Slack threads, workarounds) that fill the gaps in official process</li> <li>Build and ship AI-enabled tools, workflows, and automations directly with the analysts and teams who'll use them</li> <li>Own your tools past the demo stage — make sure the underlying data logic is sound and the tool holds up as usage scales, partnering with engineering to productionize and incorporate into enterprise tooling</li> <li>Use current AI/LLM tooling (agents, RAG, coding assistants) to build faster, and know when a lightweight tool or application is the right call versus when it needs to be a real engineered solution</li> <li>Design appropriate human review, exception handling, monitoring, and governance into each solution from the beginning</li> </ul> <p><strong>Communicate & Lead</strong></p> <ul> <li>Actively gather voice-of-client feedback from analysts and business stakeholders to determine what should be built</li> <li>Pilot new tools with a small group of real users before scaling team-wide, and use that feedback to shape the broader rollout</li> <li>Establish shared build standards, documentation practices, and governance so the team ships consistent, scalable solutions.</li> <li>Communicate technical decisions and tradeoffs clearly to non-technical stakeholders</li> <li>Confidently present your own work and reasoning to leadership</li> </ul> <ul> <li>Take ownership of a defined portion of the AI/tooling roadmap for RWDS with minimal oversight — you're expected to drive, not just execute against someone else's plan</li> <li>Mentor more junior AI solutions specialists in building scalable tooling to ensure a cohesive team approach</li> <li>Train the RWDS and dependent teams on AI tooling and maintain ongoing communication to support adoption</li> <li>Represent RWDS tooling and AI enablement work in cross-functional conversations with product, engineering, data, and other business teams</li> </ul> <p><strong>How success will be defined</strong></p> <ul> <li>Run regular 1:1s, give ongoing feedback, and own performance reviews and career growth for your direct reports</li> <li>A high-performing, engaged team that delivers against the roadmap and grows in capability over time</li> <li>Measurable improvement in business outcomes such as client experience, cost savings, revenue growth, cycle time, capacity, quality, consistency, or user experience</li> <li>Sustained adoption of deployed workflows—not simply initial usage or successful demos</li> <li>Clear evidence connecting each solution to the operational problem and expected value</li> <li>Reliable solutions with documented ownership, controls, exception paths, and success measures</li> <li>A prioritized roadmap grounded in user needs, business value, technical feasibility, and organizational readiness</li> <li>Increased capability among RWDS team members to use, improve, and identify opportunities for AI-enabled workflows</li> </ul> <p> </p> <p><strong>Required skills and experience</strong></p> <ul> <li>Able to und