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Manager, Infrastructure Project Advisory (Construction/Engineering) KPMG
San Francisco, CA1 day ago
- $110,295–$225,515 Per Year
| Location | San Francisco, CA |
| Salary | $228,000–$285,000 Per Year |
Trial Library is an AI-native enrollment and care navigation platform that accelerates access to precision medicine. In collaboration with biopharmaceutical manufacturers, payers, and health systems, Trial Library enables the delivery of clinical trials as a standard care option - improving patient access, advancing oncology outcomes, and reducing the total cost of care. Backed by leading healthcare venture capital firms, Trial Library’s platform is currently deployed in 840+ clinics and 3,000+ providers nationwide.
Lead and scale Trial Library's Engineering organization, fostering a collaborative and high-performing culture.
Partner with Product to translate business and customer needs into scalable technical solutions.
Own software architecture, engineering execution, platform reliability, and technical delivery.
Lead application engineering, AI engineering, infrastructure, DevSecOps, IT, and platform operations.
Design and build cloud-native systems supporting AI-powered products, including LLM applications, retrieval-augmented generation (RAG), AI agents, model evaluation, and production inference services.
Drive engineering excellence through modern software development practices, CI/CD, testing, observability, and operational excellence.
Build resilient, scalable infrastructure capable of supporting rapid product growth and evolving AI workloads.
Recruit, mentor, and develop high-performing engineering teams while creating an environment of continuous learning.
Partner cross-functionally with Clinical, Customer Success, Commercial, and Operations to deliver reliable customer experiences.
Ensure platform security, privacy, and compliance with HIPAA and SOC 2 requirements.
Balance engineering velocity with scalability, reliability, maintainability, and long-term technical health.
Stay current on emerging AI technologies and engineering best practices to continuously improve our platform.
8+ years of progressive software engineering experience, including engineering leadership in startup or high-growth environments.
Experience leading engineering teams responsible for building and scaling SaaS platforms.
Strong technical background in distributed systems, cloud-native architecture, APIs, and modern software engineering practices.
Experience building and operating production AI systems using large language models (LLMs), retrieval-augmented generation (RAG), AI agents, machine learning infrastructure, or related technologies.
Experience designing scalable cloud infrastructure on AWS, GCP, or Azure, including Kubernetes, CI/CD, infrastructure automation, and observability.
Demonstrated success recruiting, mentoring, and growing high-performing engineering teams.
Ability to balance rapid product delivery with platform reliability, security, and long-term maintainability.
Excellent communication skills with the ability to collaborate across departments
Experience within healthcare, life sciences, clinical research, or another regulated industry is preferred.
Familiarity with FHIR, HL7, HIPAA, and SOC 2 is a plus.
This is a hybrid role based in San Francisco, CA, with a requirement of three days per week in the office (Wednesday, Thursday, & Friday). The salary range for this position is $228,000–$285,000 per year, plus performance incentives and equity, and reflects a good faith estimate of base pay for candidates working in this location. Final compensation will be based on experience, skills, qualifications, and network depth relevant to the role.
Our interview process typically includes four stages, followed by reference checks and an offer. Depending on the role, particularly for technical or senior positions, the process may vary slightly and can include a technical assessment, case study, presentation, practical exercise, additional interview conversations, or conversations with members of our leadership team and investors.