Build the infrastructure behind the future of cancer detection
About BIOS Life
BIOS Life is a Boston-based, venture-backed healthcare technology company on a mission to fundamentally change how cancer is detected, monitored, and managed. We’re building a new model of proactive, personalized cancer care that combines advanced AI, real-world clinical data, and evidence-based medicine to help patients and clinicians make better decisions throughout the cancer journey.
Our platform brings together longitudinal patient data, predictive risk models, clinical decision support, and virtual care delivery to enable more personalized cancer screening, surveillance, and survivorship care. We’re building both the technology and clinical infrastructure to make this approach scalable, accessible, and integrated into patients’ lives.
We’re an early-stage company with an ambitious mission and a collaborative, multidisciplinary team spanning engineering, AI, clinical care, and operations. We’re looking for people who are excited to build something meaningful, solve complex problems, and help shape the future of cancer care.
We’re now hiring our first Engineering Manager to help define how we build—from technical architecture to team culture—as we move from early product to scaled, production systems.
This is a foundational leadership role: you’ll shape the engineering organization, work directly with leadership, and build systems that will directly impact patient outcomes.
What You’ll Own
Lead and grow a small, high-performing engineering team, combining hands-on technical contribution with day-to-day engineering leadership .
Lead engineering execution and day-to-day technical coordination across the application platform, partnering closely with Staff Engineers responsible for domain architecture and technical leadership.
Partner closely with the VP of Product and Engineering and PMs to translate evolving product requirements into scalable, maintainable systems.
Drive engineering quality and continuous improvement through strong technical judgment, fast feedback cycles, pragmatic process, and mentoring.
Establish and evolve engineering workflows, observability, testing practices, operational standards, and development processes as the platform grows.
Help teams make thoughtful technical and architectural tradeoffs that balance speed, maintainability, and long-term complexity management.
Contribute directly to production code and implementation work, particularly for complex or cross-cutting initiatives.
Guide pragmatic adoption of AI-assisted development workflows and automation without compromising engineering quality or system clarity.
Partner closely with clinical data engineering, infrastructure, and product teams to ensure systems integrate cleanly and evolve cohesively over time.
Help scale the engineering organization over time, including hiring, mentorship, team structure, and eventual support for additional engineering leads or managers.
What We’re Looking For
10+ years of software engineering experience , with deep hands-on technical expertise.
5+ years of engineering leadership or management experience in startup or high-growth environments.
Strong backend and application engineering experience across APIs, distributed systems, and cloud-native architectures.
Track record of balancing speed of execution with long-term maintainability and operational quality .
Experience mentoring engineers and improving team effectiveness through technical leadership, process improvement, and continuous feedback.
Strong communication and collaboration skills across engineering, product, and business stakeholders.
Ability to operate effectively in ambiguous, evolving environments and help teams navigate change pragmatically.
Comfortable contributing directly to architecture discussions, implementation, debugging, and delivery work.
Experience managing or mentoring senior and staff-level engineers is strongly preferred.
Nice to have
Experience in healthcare or regulated environments (HIPAA, SOC2, etc.).
Familiarity with clinical data systems, interoperability, or healthcare workflows.
Experience with AI-assisted development workflows or integrating AI-driven capabilities into products.
Experience scaling engineering practices and systems from early-stage through growth.
Experience across both application engineering and infrastructure/platform concerns.