[Hiring] Staff Software Engineer @SmartLight Analytics

Role Description

SmartLight Analytics is on a mission to lower the cost of healthcare by reducing wasteful spend on behalf of our self-funded customers. We are seeking a Staff Software Engineer to drive execution on key initiatives across a portfolio that spans new products, modernization of existing platforms, and re-engineering of core workflows. In this role, you will work alongside a team of senior engineers to turn product priorities into predictable delivery, shape how the team plans and ships, and help build an AI-native delivery system that increases velocity across the software development lifecycle.

This is a senior individual contributor role in which most of your impact comes through the team:

• Delegating clear ownership
• Coaching engineers
• Clearing obstacles
• Staying hands-on where it makes the biggest difference

You will work directly with the Sr. Director of Engineering on priorities, capacity, and how the team evolves, with room to grow into people leadership as the team expands.

Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, or related field, or equivalent experience
• 8+ years of professional software engineering experience, including 3+ years leading delivery of complex initiatives across a team of engineers, as an engineering manager, team lead, or staff-level engineer
• A track record of delivering complex software products through a team: planning and sequencing work, managing dependencies and risk, and meeting commitments
• Strong hands-on engineering background in designing, building, and operating production systems such as web applications, APIs, and data-intensive backend services
• Proficiency with modern AI-assisted development tools and agentic development practices, with sound judgment about where they help and where they need guardrails
• Experience building and improving delivery practices, including agile planning, CI/CD, automated testing, and release management
• Experience coaching and developing senior engineers, with a habit of delegating real ownership while holding a high bar for outcomes
• Demonstrated ability to learn a new technology stack and codebase quickly and become effective in it
• Excellent problem-solving skills, attention to detail, and accountability for production reliability
• Strong teamwork and communication skills, able to explain status, tradeoffs, and risk clearly to both technical and business audiences

Requirements

• Own end-to-end execution of major initiatives: translate roadmap priorities into realistic plans, sequence work, and keep progress and risks visible to stakeholders
• Break initiatives into well-scoped work and delegate clear ownership across the team, so delivery doesn't depend on any one person
• Help design and build an AI-native delivery system, applying AI-assisted and agentic tooling from planning through release to increase velocity without lowering the quality bar
• Partner with senior engineers and engineering leadership to turn technical direction into concrete delivery plans, raising risks and tradeoffs early enough to inform technical decisions
• Coach and mentor senior engineers on ownership, planning, estimation, and cross-team communication, supporting their growth in partnership with the Sr. Director of Engineering
• Contribute to team growth by shaping team structure and capacity plans with the Sr. Director of Engineering and playing a central role in hiring and onboarding new engineers
• Work with Product, Data Engineering, Infrastructure, and QA to clarify scope and priorities, align dependencies and release timing, and set expectations the team can meet
• Refine delivery practices, including planning cadence, work intake, definition of done, release readiness, and incident follow-up
• Make delivery health measurable, using delivery metrics and observability data to track predictability and release quality, catch regressions early, and remove bottlenecks
• Stay hands-on where it adds the most value: unblocking critical-path work, contributing to complex changes, reviewing designs and code, and building deep familiarity with the platform
• Keep delivery, including AI-assisted work, inside governance: changes move through change management, documentation stays current, and HIPAA and SOC 2 expectations are built into day-to-day work

Company Description