Principal Software Engineer
SmithRx
full-time
Posted on:
Location Type: Remote
Location: Arizona • California • United States
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Job Level
About the role
- Define and align technical strategies for multi-year, multi-team initiatives with broader company goals.
- Own technology decisions for large-scale architectures, including frameworks and build-versus-buy choices for key components.
- Design systems with high reliability, scalability, and long-term maintainability, incorporating staged validation plans where necessary.
- Ensure engineering quality through regular health reviews, curated testing strategies, and technical documentation that supports maintainability independent of your expertise.
- Drive overall testing strategies for systems requiring high reliability or quality, including creating validation frameworks or systems.
- Design platforms with long-term maintainability and embedded ML components, ensuring anomaly detection and NLP features were both scalable and production-ready.
- Collaborate with machine learning engineers to design, validate, and deploy ML-based anomaly detection systems, ensuring performance met system SLAs.
- Employ systems-level mindset to integrate ML in production environments.
- Partner with Directors, product managers, and design leadership to ensure alignment on technical strategy and business objectives.
- Collaborate with stakeholders to identify and deliver new business opportunities enabled by technical capabilities.
- Influence product decisions, scope, and technical trade-offs to prioritize customer value without compromising quality.
- Drive technical choices that have sweeping implications across the engineering organization, rallying teams around clear rationales and technical visions.
- Proactively identify and refocus engineering efforts when projects are off-course or not driving meaningful business impact.
- Partner with senior leadership to define a long-term vision for engineering teams that aligns with business and market opportunities.
- Serve as a mentor and technical guide for engineers at all levels, fostering a culture of learning and growth.
- Champion engineering excellence by setting high standards for system design, coding, testing, and operational practices.
Requirements
- BS or advanced degree in computer science or applicable experience.
- 15 years required, or 12+ years with an advanced degree of software engineering experience, including leading large-scale, complex systems or initiatives.
- Expertise in system architecture, including design for scalability, reliability, and maintainability.
- Proficiency in evaluating build-versus-buy decisions and choosing frameworks/tools for diverse use cases.
- Proven ability to design systems that address ambiguous or novel challenges, using research and validation plans to guide execution.
- Experience driving the overall health and quality of systems, including testing strategies and technical documentation.
- Strong ability to influence and align technical and product strategies across teams and stakeholders.
Benefits
- Highly competitive wellness benefits including Medical, Pharmacy, Dental, Vision, and Life Insurance and AD&D Insurance
- Flexible Spending Benefits
- 401(k) Retirement Savings Program
- Short-term and long-term disability
- Discretionary Paid Time Off
- 12 Paid Company Holidays
- Wellness Benefits
- Commuter Benefits
- Paid Parental Leave benefits
- Employee Assistance Program (EAP)
- Well-stocked kitchen in office locations
- Professional development and training opportunities
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
system architecturescalabilityreliabilitymaintainabilitymachine learninganomaly detectionnatural language processingtesting strategiestechnical documentationbuild-versus-buy evaluation
Soft Skills
influencecollaborationmentorshipstrategic alignmentproblem-solvingleadershipcommunicationtechnical guidanceculture of learningbusiness impact focus
Certifications
BS in computer scienceadvanced degree in computer science