Play a critical hands-on role in building the AI-powered intelligence layer of the Pearl platform
Design and implement Applied AI features, including RAG pipelines, Agentic workflows, and LLM integrations
Develop high-performance data pipelines, APIs, and microservices that process healthcare data at scale
Execute Proof-of-Concepts (POCs) and technical evaluations of new AI technologies
Build responsive web applications using modern frontend frameworks
Ensure observability, monitoring, and operational excellence for AI-powered services
Drive architectural decisions and system optimizations for AI features
Mentor and upskill fellow engineers on Applied AI best practices
Own and deliver complex technical projects with autonomy and accountability

Requirements

5-8+ years of professional experience in software engineering
Hands-on experience building and productionizing Applied AI/LLM features
Experience with observability and evaluation practices for production LLM systems
Strong proficiency in Python, relational databases, and a major cloud platform (AWS preferred)
A deep understanding of modern service design principles
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.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonApplied AILLM integrationsdata pipelinesAPIsmicroservicesobservabilityperformance optimizationreliability engineeringsecurity best practices

Soft Skills

mentoringautonomyaccountabilitytechnical best practicesteam collaboration