Solution Engineer Intern at Kpler dedicated to empowering organizations with insights for informed decisions. Actively learn product features and deliver key project tasks.
About the role
- GenAI Solutions Engineer developing and implementing AI solutions for healthcare at Tempus. Collaborating with sales teams to address customer needs and enhance operational efficiency.
Responsibilities
- Embed directly within the sales team to help identify real problems and solve them using agentic GenAI solutions built on the Tempus OS platform
- 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 — from workflow automation to patient communication, insight generation, or clinical operations
- Enable customer leaders by revolutionizing their processes to enhance their healthcare provider engagement and experience through AI-derived actions and insights
- Build rapid prototypes / proof-of-concepts to validate ideas and alignment
- Work directly with LLMs and agent frameworks (prompt design, chaining, context management, evaluation, and guardrails)
- Lead moderate-to-full implementations in collaboration with customer teams or internal engineers
- Build integrations between customer data systems, APIs, and Tempus OS services
- Configure, test, iterate, tune performance, and ensure reliability
- Evangelize best practices in AI safety, observability, and responsible deployment
- Serve as the customer’s technical and strategic bridge to Tempus — shaping our roadmap through real-world feedback
- 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
Requirements
- 5+ years in technical/customer-facing roles (solutions engineering, AI/ML implementation, systems architecture)
- Hands-on experience building or deploying GenAI applications (agents, chat interfaces, or LLM-driven workflows)
- Strong programming skills (Python, JavaScript or similar) and familiarity with APIs, webhooks, integration patterns, data pipelines
- Experience designing or building prototype-to-production AI solutions (not just proof-of-concepts) — including observability, A/B testing, error-handling, scaling
- Familiarity with prompt engineering, RAG, model evaluation, and orchestration frameworks (LangChain, LlamaIndex, or similar)
- Excellent communication and storytelling skills — able to interface with both clinicians and engineers
- Proven ability to drive projects from discovery through delivery, 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
- Familiarity with frameworks or tools such as LangChain, Retrieval-Augmented Generation (RAG), agent orchestration frameworks
- Experience or understanding working with CRM platforms (e.g. Salesforce) and data visualization tools (e.g. Looker, Tableau)
Benefits
- Incentive compensation
- Restricted stock units
- Medical and other benefits
Job title
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Degree requirement
No Education Requirement
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