Job Opportunities API

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 Requirements 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 exper