Senior Software Engineer, Full Stack

Chartis

13d•$200,000 - $225,000•Remote

About The Position

This is an opportunity to join a software development team building next-generation AI platforms for healthcare. We are looking for a technically fearless, accomplished engineer who will serve as a subject matter expert across agentic and full-stack systems, working daily in an agile environment to solve complex, cross-team challenges. You will drive engineering excellence and champion a culture of quality, innovation, and operational effectiveness.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, Mathematics, or a related scientific/engineering field.
5+ years of relevant industry experience shipping world-class products as part of a highly functional software development team.
Demonstrated experience designing and maintaining AI infrastructure and agentic workflows utilizing frameworks such as LangChain, LangGraph, Google ADK, or similar.
Extensive hands-on experience in full-stack software development with proficiency in Python, Node.js, and JavaScript/TypeScript, including front-end frameworks (e.g., React, Next.js) and back-end API design.
Deep technical proficiency with cloud platforms (Azure or Google Cloud), including experience with managed AI services, vector/semantic search, and cloud-native deployment patterns.
Strong understanding of CI/CD, Infrastructure as Code (IaC), and containerized workloads (Kubernetes), with demonstrated experience supporting production systems.
Proven ability to translate complex technical decisions and engineering tradeoffs into business risk and impact for non-technical stakeholders, and to represent platform constraints clearly in cross-functional planning.

Nice To Haves

Master’s degree preferred.
Familiarity with deploying AI PaaS solutions such as Azure AI Foundry or Vertex AI is a plus.

Responsibilities

Design and build robust agentic workflows utilizing advanced frameworks such as LangChain and LangGraph.
Contribute to the strategy and ongoing maintenance of AI infrastructure, ensuring alignment with broader business goals and organizational risk tolerance.
Develop and maintain robust AI evaluation frameworks that measure real-world performance and drive measurable outcomes in healthcare.
Develop indexing and retrieval strategies across diverse healthcare data sources, including document repositories, FHIR-based clinical datasets, and payor/provider data, to power intelligent, context-aware applications.
Lead deployment of Large Language Models (LLMs) at scale, ensuring reliability, performance, and responsible AI safety practices.
Build scalable back-end services and front-end solutions, utilizing languages and frameworks such as Python, Node.js, and JavaScript/TypeScript.
Define and maintain reliable cloud infrastructure using Infrastructure as Code (IaC) best practices on Azure or Google Cloud.
Ensure robust CI/CD pipelines are in place for automated deployment, testing, and continuous quality assurance.
Champion best practices for observability, availability, latency, scalability, and efficiency across distributed systems.
Build solutions with a DevOps mindset, seeking to automate integration and deployment so features can scale effectively and securely.
Mentor other engineers through code reviews, design documentation, and post-mortems to foster a culture of technical growth.
Lead the technical direction of products through roadmaps and design reviews, translating engineering tradeoffs into business risk and impact for non-technical stakeholders.
Partner effectively across multiple teams and with Product and UX stakeholders to ensure platform decisions reflect business requirements.
Demonstrate excellent judgment in selecting methods for developing solutions that are robust, reliable, testable, and maintainable.
Maintain a voracious appetite for current technology trends, continuously bringing relevant innovations to the team.