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Trial LibrarySan Francisco, CA
Head of Engineering
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On-siteFull Time$228k - $285k per yearPosted 37 days ago
About the role
- Trial Library is seeking an experienced Head of Engineering to lead our engineering organization and build the next generation of our AI-native platform
- You will lead Engineering and Infrastructure while partnering closely with Product to deliver secure, scalable, and high-performing software
- This is a hands-on leadership role for an engineering leader who enjoys solving complex technical challenges, building production AI systems, and mentoring exceptional engineering teams in a fast-paced startup environment
- You’ll help shape the technical direction of our platform while remaining deeply engaged in architecture, engineering execution, and technical decision-making
- 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
- Meaningful impact — helping patients access clinical trials faster through better technology and workflows
- High ownership environment — autonomy to build, test, and influence strategy across the business
- Collaborative team culture — low ego, high trust, and close partnership across functions
- Opportunity for growth — join at an early stage with meaningful exposure to company-building and decision-making Benefits
- We are a remote-based, fast growth team
- All full-time employees receive paid vacation and parental leave
- We provide a competitive salary & equity compensation
- We offer technology tools and a work-from-home setup stipend
- We offer medical, dental, and vision coverage to our employees
- We value career development for all
- Demonstrated success recruiting, mentoring, and growing high-performing engineering teams
- Experience leading engineering teams responsible for building and scaling SaaS platforms
- Experience within healthcare, life sciences, clinical research, or another regulated industry is preferred
- Experience building and operating production AI systems using large language models (LLMs), retrieval-augmented generation (RAG), AI agents, machine learning infrastructure, or related technologies
- Excellent communication skills with the ability to collaborate across departments
- Experience designing scalable cloud infrastructure on AWS, GCP, or Azure, including Kubernetes, CI/CD, infrastructure automation, and observability
- Familiarity with FHIR, HL7, HIPAA, and SOC 2 is a plus
- Ability to balance rapid product delivery with platform reliability, security, and long-term maintainability
- 8+ years of progressive software engineering experience, including engineering leadership in startup or high-growth environments
- Strong technical background in distributed systems, cloud-native architecture, APIs, and modern software engineering practices
- 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