Software Engineer I

United StatesRemoteFull Time

Software EngineerSoftware Engineering

0 views0 saves0 applied

Apply Now

Quick Summary

Overview

As a Software Engineer I at Aledade, we maintain, improve, and expand our web application and data pipelines.

Technical Tools

Software EngineerSoftware Engineering

As a Software Engineer I at Aledade, we maintain, improve, and expand our web application and data pipelines. We're looking for engineers who know that writing new code is not always the solution to a problem, but when technological changes are needed they create secure, maintainable, performant, correct, scalable, and stable solutions to the complex and unique challenges in our corner of the healthcare industry.

They embrace strategies that minimize risk, leaning towards observability, alerting, metrics, high test coverage, and frequent releases that incrementally build value.

Develop and implement scalable and performant solutions.

Partner, as a peer, with Engineering Managers, Product Managers, and stakeholders throughout Aledade to develop and execute technical roadmaps using Agile processes.

BS/BTech (or higher) in Computer Science, Engineering or a related field.

1+ years experience as an engineer building full-stack web applications as part of a cross-functional team.

1+ years of experience working with SQL or other database querying language on large multi-table data sets.

Experience building a full stack web applications in any language/framework.

Proficiency with CSS/HTML/Javascript and modern JavaScript frameworks (e.g., React, Angular, VueJs/Ember).

Expertise in at least 1 server-side web technology (eg: Nodejs, Java, Python, Scala, C#, C++,Go, JVM).

Familiarity with relational database systems.

Experience with API design and development.

Experience with cloud based technologies such as AWS, Azure or google cloud.

Knowledge of containerization and orchestration technologies such as Docker and Kubernetes.

Familiarity with continuous integration and continuous deployment(CI/CD) pipelines.

Experience with security and systems that handle sensitive data.

Proficiency in machine learning algorithms and techniques.

Experience in deploying machine learning models into production environments.

Expertise with statistical data techniques (such as causal inference, syntactic analysis, sampling methods, NLP etc), with experience in addressing challenges from incomplete, unrepresentative, and mislabeled data.

Experience with cloud computing platforms such as AWS, Azure or Google Cloud.

Experience with security and systems that handle sensitive data.

Sitting for prolonged periods of time. Extensive use of computers and keyboard. Occasional walking and lifting may be required.