Senior Software Engineer (Applied AI)
P
Pearl HealthHealthcare
Seattle, New York City, BostonFull-TimeSenior
Salary130000 - 200000 USD per year
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Job Details
- Experience
- 5-8+ years
- Required Skills
- AWSPythonMicroservicesDistributed Systems
Requirements
- 5-8+ years of professional experience in software engineering
- Strong foundation in service-oriented architectures and distributed systems
- Hands-on experience building and productionizing Applied AI/LLM features (RAG architectures, vector databases, embedding models, Agentic workflows)
- Experience with observability and evaluation practices for production LLM systems (prompt tracking, quality metrics, cost monitoring)
- Strong proficiency in Python
- Strong proficiency in relational databases
- Proficiency in a major cloud platform (AWS preferred)
- Deep understanding of modern service design principles, including RESTful and event-driven architectures
- Proven experience designing, building, and optimizing data-intensive applications
- Demonstrated history of mentoring engineers and driving technical best practices within a team
- Strong background in performance optimization, reliability engineering, and security best practices
Responsibilities
- Design, build, and own production AI features powered by LLMs, including RAG architectures 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).
- 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.
- 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.
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