Senior Software Engineer

What You'll Do

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.

What You'll Bring

Must-Haves

• 7+ years of professional experience in software engineering, with a strong foundation in service-oriented architectures and distributed systems.
• Hands-on experience working with RAG architectures, vector databases, embedding models, and/or Agentic workflows in personal or production environments.
• Experience with observability and evaluation practices for 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.

Nice-to-Haves

• 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; if your career preference is to specialize deeply in only one area of the stack (pure frontend or pure backend); or if you thrive most in a highly structured corporate environment with top-down decision-making and minimal ambiguity.

What We Offer

Base Salary Range: $160,000 - $200,000 per year.
Additional Compensation: Eligible for a discretionary performance bonus and equity options.
Benefits: Competitive benefits package (details on careers page).
Final compensation determined by skills, experience, labor market conditions, and location.