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As a Senior Software Engineer (Applied AI), you will play a critical hands-on role in building the AI-powered intelligence layer of the Pearl platform. You will design and implement Applied AI features, including RAG pipelines, Agentic workflows, and LLM integrations, while ensuring these capabilities are delivered through scalable, production-grade services.
Job Responsibility:
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)
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
Requirements:
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
Nice to have:
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