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# Software Engineer and Data Integrator

- **Company:** Intezra, Inc.
- **Location:** Columbia, MD, United States
- **Experience:** Experienced
- **Salary:** $160,000.0 - $190,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), JavaScript (Programming Language), Artificial Intelligence, Amazon Web Services, Systems Engineering, Confluence, JIRA, Microsoft Azure, Big Data, Computer Networks, DevOps, Python (Programming Language), Machine Learning, Software Engineering, Web Applications, Large Language Models, Git, Kubernetes, Atlassian Tools, Bitbucket, Docker, Programming Languages
- **Published:** September 27, 2026
- **Apply:** https://www.juju.com/job/16_7f6a4329

## About the Role

* 8+ years with a Bachelor's degree, OR
 * 6+ years with a Master's degree, OR
 * 4 additional years of relevant experience in lieu of a degree, * Experience using AI, LLMs, and leveraging the latest technologies.
 * Production-grade software development experience in Python.
 * Experience with deployment and management of services in cloud-based hosting environments such as AWS or Azure.
 * Service containerization and deployment with Docker/Kubernetes.
 * Familiarity with Git / Bitbucket.
 * Documentation using Atlassian Tools (Jira, Confluence).

Nice to Haves

 * Experience with additional programming languages (Java, C).
 * Experience prototyping web applications (JavaScript).
 * Full-stack development.
 * Analyzing cybersecurity-related datasets (network traffic, OS events).

## Description

You will act as a general-purpose Software Engineer and Data Integrator for an up-and-coming project where you will design, develop, and integrate solutions involving the analysis of large data sets to provide high-impact insights.

You'll work closely with analysts, data scientists, other software and systems engineers, and systems administrators to integrate AI/ML technologies into the platform.

Responsibilities

 * Build upon Docker / Kubernetes experience.
 * Build scripts to convert and normalize data.
 * Leverage DevOps experience.
 * Leverage AI experience.
 * Elicit requirements from stakeholders and determine the applicability of AI and Machine Learning solutions.


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