Remote Mid Level Backend Engineer for Healthcare Company
Pearl • Central Visayas, Philippines • Bogotá, Bogota, Colombia
Posted: July 13, 2026
Job Description
Work From Anywhere in LATAM
Work Schedule: EST | Full overlap with US Eastern business hours (Monday–Friday)
About Pearl Talent
Pearl works with the top 1% of candidates from around the world and connects them with the best startups in the US and EU. Our clients have raised over $5B in aggregate and are backed by companies like OpenAI, a16z, and Founders Fund.
Hear why we exist, what we believe in, and who we're building for: Watch here
About the Client
A seed-stage healthcare technology company is building the data infrastructure that powers smarter, faster healthcare coverage decisions, and is hiring a Senior Backend Engineer to own that infrastructure end-to-end.
The company aggregates and normalizes more than 100,000 medical policies from over 100 payers into a searchable database, using AI systems to turn dense payer rules into actionable insights. Backed by several early-stage accelerators and investors, the team recently landed a commercial partnership and is now scaling its applied AI systems.
About the Role
You'll join a lean, founder-led engineering team as the Senior Backend Engineer, reporting directly to the founder and acting as technical lead for a small group of part-time and offshore engineers — reviewing code and shaping architectural decisions without formal people-management responsibility. You'll own the end-to-end web scraping and data ingestion pipeline, use LLMs to structure unstructured payer policy data, and build the CI/CD and reliability systems the platform runs on.
Core Responsibilities
Web Scraping Infrastructure & Platform Development
- Build and scale platform infrastructure for web scrapers collecting policy data from 100+ healthcare payers
- Improve scraper reliability and scalability without sacrificing data accuracy
- Own the end-to-end scraper pipeline from data ingestion to storage
- Resolve infrastructure bottlenecks blocking new scraper development
LLM-Powered Data Normalization & Structuring
- Use LLM systems to transform unstructured payer policy text into structured, searchable data
- Infer and tag relevant medical codes from policy language using AI models
- Determine coverage status for procedures based on LLM-driven analysis
- Build evaluation and testing harnesses to validate AI system output quality
CI/CD, Job Reliability & System Ownership
- Build and maintain CI/CD pipelines for testing and deploying scraper jobs
- Improve reliability of scraper job infrastructure through monitoring and fixes
- Diagnose and resolve system issues across the data pipeline
- Own architectural decisions and communicate them to the engineering team
API Design & Data Product Development
- Design and maintain APIs serving normalized policy data to customers
- Support the Snowflake-based data product used by client customers
- Ensure data outputs are structured for downstream usability
Must-Have
- 3-5 years of professional backend engineering experience with demonstrated ownership of production data pipelines or platform-level systems
- Expert-level Python proficiency (3+ years in a professional backend engineering context)
- Strong SQL experience, including complex queries and schema design (Postgres or equivalent relational database)
- Hands-on cloud infrastructure experience deploying and managing services (AWS preferred; Azure or GCP with 2+ years accepted)
- Demonstrated experience working with messy, unstructured, or ambiguous data sources (data normalization, cleaning, or ingestion from inconsistent external sources)
- Experience owning CI/CD pipeline design and implementation for testing and deployment
- Client-facing English proficiency at B2+ (CEFR)
Nice-to-Have
- Experience building or productionizing LLM-based systems with evaluation or testing components (not limited to API calls)
- Web scraping framework experience (Scrapy, Playwright, or similar)
- Experience with RAG (Retrieval-Augmented Generation) pipelines
- Prior experience in healthcare, fintech, or another highly regulated data domain
- Infrastructure-as-Code experience (Terraform) or familiarity with FastAPI/Snowflake
Additional Content
Work From Anywhere in LATAM
Work Schedule: EST | Full overlap with US Eastern business hours (Monday–Friday)
About Pearl Talent
Pearl works with the top 1% of candidates from around the world and connects them with the best startups in the US and EU. Our clients have raised over $5B in aggregate and are backed by companies like OpenAI, a16z, and Founders Fund.
Hear why we exist, what we believe in, and who we're building for: Watch here
About the Client
A seed-stage healthcare technology company is building the data infrastructure that powers smarter, faster healthcare coverage decisions, and is hiring a Senior Backend Engineer to own that infrastructure end-to-end.
The company aggregates and normalizes more than 100,000 medical policies from over 100 payers into a searchable database, using AI systems to turn dense payer rules into actionable insights. Backed by several early-stage accelerators and investors, the team recently landed a commercial partnership and is now scaling its applied AI systems.
About the Role
You'll join a lean, founder-led engineering team as the Senior Backend Engineer, reporting directly to the founder and acting as technical lead for a small group of part-time and offshore engineers — reviewing code and shaping architectural decisions without formal people-management responsibility. You'll own the end-to-end web scraping and data ingestion pipeline, use LLMs to structure unstructured payer policy data, and build the CI/CD and reliability systems the platform runs on.
Core Responsibilities
Web Scraping Infrastructure & Platform Development
- Build and scale platform infrastructure for web scrapers collecting policy data from 100+ healthcare payers
- Improve scraper reliability and scalability without sacrificing data accuracy
- Own the end-to-end scraper pipeline from data ingestion to storage
- Resolve infrastructure bottlenecks blocking new scraper development
LLM-Powered Data Normalization & Structuring
- Use LLM systems to transform unstructured payer policy text into structured, searchable data
- Infer and tag relevant medical codes from policy language using AI models
- Determine coverage status for procedures based on LLM-driven analysis
- Build evaluation and testing harnesses to validate AI system output quality
CI/CD, Job Reliability & System Ownership
- Build and maintain CI/CD pipelines for testing and deploying scraper jobs
- Improve reliability of scraper job infrastructure through monitoring and fixes
- Diagnose and resolve system issues across the data pipeline
- Own architectural decisions and communicate them to the engineering team
API Design & Data Product Development
- Design and maintain APIs serving normalized policy data to customers
- Support the Snowflake-based data product used by client customers
- Ensure data outputs are structured for downstream usability
Must-Have
- 3-5 years of professional backend engineering experience with demonstrated ownership of production data pipelines or platform-level systems
- Expert-level Python proficiency (3+ years in a professional backend engineering context)
- Strong SQL experience, including complex queries and schema design (Postgres or equivalent relational database)
- Hands-on cloud infrastructure experience deploying and managing services (AWS preferred; Azure or GCP with 2+ years accepted)
- Demonstrated experience working with messy, unstructured, or ambiguous data sources (data normalization, cleaning, or ingestion from inconsistent external sources)
- Experience owning CI/CD pipeline design and implementation for testing and deployment
- Client-facing English proficiency at B2+ (CEFR)
Nice-to-Have
- Experience building or productionizing LLM-based systems with evaluation or testing components (not limited to API calls)
- Web scraping framework experience (Scrapy, Playwright, or similar)
- Experience with RAG (Retrieval-Augmented Generation) pipelines
- Prior experience in healthcare, fintech, or another highly regulated data domain
- Infrastructure-as-Code experience (Terraform) or familiarity with FastAPI/Snowflake