Job description

At Latica, our goal is to unlock the value of data to transform patient care. We're building a secure data network and medical intelligence platform that gives the healthcare ecosystem rapid, safe access to de-identified real-world health and patient data, accelerating R&D, improving diagnostics, and ultimately saving lives. We were founded by repeat entrepreneurs and recognized leaders in healthcare, data science, AI, and cybersecurity. We look for people who are smart, open, and fun to work with. We invest in our team and believe in hiring high-potential, humble individuals who can grow rapidly as we scale. Are you ready to help build the engineering foundation that changes how the world understands and treats disease? WHAT YOU’LL DO • Design and architect complex, scalable systems end-to-end. Making principled tradeoffs between performance, reliability, maintainability, and cost, and owning those decisions from whiteboard to production • Design, build, and own scalable data pipelines for real-world health data from diverse sources • Architect and implement production-grade AI-driven services for high-scale analysis of medical data. • Build and operate robust backend services, APIs, and data products end-to-end. You design it, you build it, you run it • Tackle genuinely hard distributed systems problems: low-latency access patterns, fault tolerance, consistency at scale • Plan and build connection layers for EHR platforms and health APIs within isolated network environments • Own cloud infrastructure end-to-end. Build systems that are repeatable, observable, and easy to change • Drive engineering excellence: rigorous code and architecture reviews, testing strategies, and observability frameworks • Partner with Data Science, Product, and Business to turn ambiguous requirements into production-grade solutions WHO YOU ARE • 5+ years building production software systems; care deeply about coding craft • Fluent in Python, MCP and high scale / high throughout data pipelines • Strong grasp of distributed systems, software architecture, and engineering fundamentals • Experienced in building complex data pipelines and cloud-native systems on AWS • Think holistically about correctness, performance, security, and cost • Self-directed, clear communicator, thrive in a fast-moving startup with high ownership • Genuinely excited by the mission: applying great engineering to improve patient outcomes EXTRA CREDIT • Experience in building a Large Language Model (LLM) pipeline (e.g., Qwen, Llama) • Experience working with medical or clinical data (EHR, FHIR, HL7, claims, or de-identified patient datasets) • Familiarity with data standardization frameworks, data cataloguing, or metadata management • Experience with HIPAA compliance, data privacy, or healthcare security requirements • Exposure to ML pipelines, feature stores, or working with data science teams • A bachelor’s, master’s, or PhD in Computer Science or a related quantitative field TECH STACK Python · AWS · PostgreSQL · Elasticsearch · Terraform · Airflow / Prefect

Requirements

Must-haves

Are you ready to help build the engineering foundation that changes how the world understands and treats disease?
Design and architect complex, scalable systems end-to-end. Making principled tradeoffs between performance, reliability, maintainability, and cost, and owning those decisions from whiteboard to production
Design, build, and own scalable data pipelines for real-world health data from diverse sources
Architect and implement production-grade AI-driven services for high-scale analysis of medical data.
Build and operate robust backend services, APIs, and data products end-to-end. You design it, you build it, you run it
Tackle genuinely hard distributed systems problems: low-latency access patterns, fault tolerance, consistency at scale
Plan and build connection layers for EHR platforms and health APIs within isolated network environments
Own cloud infrastructure end-to-end. Build systems that are repeatable, observable, and easy to change
Drive engineering excellence: rigorous code and architecture reviews, testing strategies, and observability frameworks
Partner with Data Science, Product, and Business to turn ambiguous requirements into production-grade solutions
5+ years building production software systems; care deeply about coding craft
Fluent in Python, MCP and high scale / high throughout data pipelines
Strong grasp of distributed systems, software architecture, and engineering fundamentals
Experienced in building complex data pipelines and cloud-native systems on AWS
Think holistically about correctness, performance, security, and cost
Self-directed, clear communicator, thrive in a fast-moving startup with high ownership
Genuinely excited by the mission: applying great engineering to improve patient outcomes
Python · AWS · PostgreSQL · Elasticsearch · Terraform · Airflow / Prefect

Nice-to-haves

Experience in building a Large Language Model (LLM) pipeline (e.g., Qwen, Llama)
Experience working with medical or clinical data (EHR, FHIR, HL7, claims, or de-identified patient datasets)
Familiarity with data standardization frameworks, data cataloguing, or metadata management
Experience with HIPAA compliance, data privacy, or healthcare security requirements
Exposure to ML pipelines, feature stores, or working with data science teams
A bachelor’s, master’s, or PhD in Computer Science or a related quantitative field

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aipythonawsllmml

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