Senior Software Engineer, Data Products

Lynx MD, Ltd.
Palo Alto, CA, United States
23 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Clinical Data Repository Cloud Computing Data Governance Distributed Systems Fault Tolerance Python (Programming Language) Meta-Data Management Software Architecture Strategies of Testing
+10 more
EHR Systems Fast Healthcare Interoperability Resources Large Language Models Electronic Medical Records Information Technology Low Latency Health Level Seven International Build Tools Machine Learning Operations Data Pipelines

Job description

  • 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

Requirements

  • 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

About the company

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?

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.indeed.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

5:48 min

Balancing delivery latency with stream reliability and scale

Phil Cluff · LIVE

48 sec

Exploring alternative build tools and experimental web components

Sasha Shynkevich · LIVE

3:03 min

Building an AI operating system for clinical diagnostics

Alexandre Guenoun Alexandre Guenoun +3 · World Congress 2026 Europe

3:37 min

Accessing API documentation and testing remote driving latency

Alexandru Ciinaru Alexandru Ciinaru +3 · World Congress 2025

2:09 min

Configuring IDEs and build tools for Java 17

Daniel Strmečki · LIVE

3:30 min

Scaling agile frameworks and data interoperability in healthcare

Leo Lindhorst · World Congress 2022

Videos

See all

Related articles

See all