Customer Success AI Strategy & Agent Development Lead

About the role

Tempus is seeking a Senior GenAI Solutions Engineer to join our team. This role sits at the intersection of operations, product management, and solutions architecture to drive AI implementation and innovation.

Responsibilities

• Embed deeply with Customer Success and Commercial organizations as their dedicated AI Strategy Lead, reimagining the Customer Success model to be agentic-first.
• Work with leadership to audit the organization, lead the vision of the future, and build the agentic infrastructure to drive an elevated customer success experience for care teams and improve patient care.
• Expand scope across the Tempus OS ecosystem, bringing scalable GenAI frameworks to additional teams and external health systems and life sciences partners.
• Partner with customer leaders to uncover high-impact use cases where GenAI and Tempus OS can deliver measurable value.
• Design and implement agent-based solutions, ranging from workflow automation to patient communication, insight generation, or clinical operations.
• Build rapid prototypes and proof-of-concepts to validate ideas and align with stakeholders.
• Lead moderate-to-full implementations in collaboration with customer teams or internal engineers.
• Configure, test, iterate, tune performance, and ensure reliability of deployed agents.
• Evangelize best practices in AI safety, observability, and responsible deployment.
• Create solution templates, reference architectures, and internal learning artifacts that make future deployments faster and safer.
• Train business users, power users, and internal champions on interacting with deployed agents.

Qualifications

• 5+ years in technical or customer-facing roles, such as solutions engineering, AI/ML implementation, or systems architecture.
• Hands-on experience building or deploying GenAI applications, including agents, chat interfaces, or LLM-driven workflows.
• Strong programming skills (Python, JavaScript, or similar) and familiarity with APIs, webhooks, integration patterns, and data pipelines.
• Experience designing or building prototype-to-production AI solutions (not just proof-of-concepts), including observability, A/B testing, error-handling, and scaling.
• Familiarity with prompt engineering, RAG, model evaluation, and orchestration frameworks like LangChain, LlamaIndex, or similar.
• Excellent communication and storytelling skills, with the ability to interface smoothly with both clinicians and engineers.
• Proven ability to drive projects from discovery through delivery, successfully balancing experimentation and execution.

Preferred Experience

• In healthcare, life sciences, or regulated industries.
• Understanding of data privacy, PHI handling, and compliance in AI systems.
• Experience working with customers who have limited engineering resources.
• Track record of creating demos, proofs of concept, or internal enablement tools that accelerate adoption.