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# Mid-Level Software Engineer

- **Company:** NEURAL SOLUTIONS LLC
- **Location:** Columbia, MD, United States
- **Experience:** Experienced
- **Salary:** $148,000.0 - $177,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), JavaScript (Programming Language), Artificial Intelligence, Amazon Web Services, Confluence, JIRA, Microsoft Azure, Big Data, Cloud Computing, Signals Intelligence, Cyber Security, Computer Networks, Data Files, DevOps, Systems Analysis, Python (Programming Language), Machine Learning, Software Engineering, Web Applications, Large Language Models, Git, Kubernetes, Atlassian Tools, Bitbucket, Docker, Programming Languages
- **Published:** July 16, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9032932/mid-level-software-engineer

## About the Role

* Experience using AI, LLMs, and latest technologies.
 * Production-grade software development experience in Python.
 * Experience with deployment and management of services in cloud-based environments such as AWS/Azure.
 * Service containerization and deployment with Docker/Kubernetes.
 * Familiarity with Git / Bitbucket.
 * Documentation using Atlassian Tools (Jira, Confluence).

 * Experience with additional programming languages such as Java or C.
 * Experience prototyping web applications in JavaScript.
 * Full Stack Development skills.
 * Ability to analyze cyber security-related data sets (network traffic, OS events).
 * Familiarity with signals intelligence collection and analysis systems.
 * Knowledge of advanced security operations.

Experience Required: 8 years with Bachelor's degree in a technical discipline or 12 years without degree

## Description

This role involves designing, developing, and integrating solutions that analyze large data sets to provide mission-centric insights. You will collaborate with analysts, data scientists, software/system engineers, and systems administrators using AI/ML technologies.

 * Build upon Docker / Kubernetes experience.
 * Create scripts for converting and normalizing data.
 * Leverage DevOps expertise.
 * Utilize AI knowledge to solve complex problems.
 * Elicit requirements from stakeholders and determine the applicability of AI/ML solutions.


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