Senior Software Engineer (Applied AI)
RemoteSeniorNAArtificial IntelligenceFintechCloud ComputingSenior Software EngineerEngineering ManagerFellowPatient CareFull StackAWSPythonVector
Upload My Resume
Drop here or click to browse · PDF, DOCX, TXT
Requirements
- You are an experienced engineer who combines strong full-stack fundamentals with hands-on Applied AI experience. You're excited to build production AI systems in a fast-moving healthcare environment and to elevate the capabilities of the team around you.
- 5-8+ years of professional experience in software engineering, with a strong foundation in service-oriented architectures and distributed systems.
- Hands-on experience building and productionizing Applied AI/LLM features, including working with RAG architectures, vector databases, embedding models, and/or Agentic workflows.
- Experience with observability and evaluation practices for production LLM systems (prompt tracking, quality metrics, cost monitoring)
- Strong proficiency in Python, relational databases, and a major cloud platform (AWS preferred).
- A deep understanding of modern service design principles, including RESTful and event-driven architectures.
- Proven experience designing, building, and optimizing data-intensive applications.
- A demonstrated history of mentoring engineers and driving technical best practices within a team.
- A strong background in performance optimization, reliability engineering, and security best practices.
- Experience building and deploying user-facing client applications using modern frameworks (e.g., React, Angular, Vue.js, TypeScript).
- A background working in healthcare technology, fintech, or another highly regulated industry.
- Familiarity with compliance and security frameworks such as HIPAA or SOC2.
- This role might not be for you if:
- You are primarily interested in academic AI research or fundamental model training, rather than the hands-on productization and deployment of AI features.
- Your career preference is to specialize deeply in only one area of the stack (pure frontend or pure backend) and not apply expertise across a full-stack context.
- You thrive most in a highly structured corporate environment with top-down decision-making and minimal ambiguity.
- Collaborate to Innovate: We believe the best solutions arise from intelligent teamwork. We trust the expertise of our teammates and pursue opportunities to learn and grow from each other. By embracing diverse perspectives and encouraging authenticity, we create and evangelize groundbreaking health solutions.
- Trust Through Transparency: We prioritize transparency in all our interactions, ensuring that employees, patients, clinicians and partners have access to the information they need to make informed decisions. Integrity is at the core of how we operate, from building products to fostering relationships, and is crucial to our ability to communicate openly and gain trust.
- Serious Impact, Big Heart: We go above and beyond with our efforts to empower proactive, patient-centered care — and we celebrate every step forward. Humor and positivity fuel our creativity, strengthen relationships, and remind us to acknowledge the journey as much as the destination.
- Engineering Manager Interview: A deeper-dive conversation with an EM.
- Panel Interview: A round of technical and behavioral meetings with teammates, a cross-functional partner, and a leader.
- Executive Interview: Final conversation(s) with 1-2 of our leaders.
Responsibilities
- Applied AI & Full-Stack Engineering
- Design, build, and own production AI features powered by LLMs, including RAG architectures (chunking strategies, semantic search, vector databases) and Agentic workflows.
- Develop high-performance data pipelines, APIs, and microservices that process healthcare data at scale and securely integrate LLM outputs into user-facing experiences.
- Execute Proof-of-Concepts (POCs) and technical evaluations of new AI technologies to validate product viability and scalability.
- Build responsive web applications using modern frontend frameworks to deliver intuitive, user-facing intelligence and analytic features.
- Ensure observability, monitoring, and operational excellence for AI-powered services, championing security and regulatory compliance (HIPAA, SOC2).
- Technical Leadership & Collaboration
- Drive architectural decisions and system optimizations for AI features in close collaboration with product and engineering leadership.
- Own technical projects from discovery to delivery with autonomy, ensuring solutions align with business needs and long-term scalability.
- Mentor and upskill fellow engineers on Applied AI best practices, fostering a strong culture of technical excellence and collaborative growth.
- Contribute to the team's understanding of LLM capabilities, limitations, and best practices within the healthcare domain.
- Participate in thorough design and code reviews, raising the bar for technical quality across the team.
- Delivery & Impact
- Own and deliver complex technical projects with autonomy and accountability, ensuring successful delivery aligned with business timelines.
- Identify and help resolve technical bottlenecks and cross-team dependencies that impact delivery velocity or system reliability.
- Balance speed and quality, making pragmatic decisions that enable rapid iteration while maintaining engineering excellence.
Benefits
- The expected offer for this role includes the following components:
- Base Salary Range: $130,000 - $200,000 per year.
- Additional Compensation: This role is eligible for a discretionary performance bonus and equity options.
- Benefits: We offer a competitive benefits package. More on our careers page.
- Final compensation for this role will be determined by a variety of factors, including a candidate's relevant skills, experience, labor market conditions, and location.
- The Interview Process
- While steps may vary by role, you can typically expect:
Similar Jobs
13h ago