Bachelor's degree in Engineering, Computer Science, Math, or related field.
2+ years of experience in software design, development, and debugging.
Strong proficiency in modern programming languages like Java or Python.
Experience with microservices architectures and REST APIs using Spring Boot.
Familiarity with AI/ML technologies and tools like TensorFlow or PyTorch.
Experience with Docker and Kubernetes for containerization.
Knowledge of cloud platforms such as AWS, Azure, or Google Cloud.
Responsibilities
Design, develop, test, and deploy scalable applications and microservices.
Integrate AI capabilities and machine learning models into applications.
Participate in architecture and design reviews for scalability and security.
Collaborate with cross-functional teams in DevOps, cybersecurity, and QA.
Document technical specifications including system architecture and APIs.
Monitor and troubleshoot distributed applications in production.
Apply secure coding practices in accordance with DevSecOps workflows.
Benefits
Remote work options available or location in Marlton, NJ area.
Standard Monday to Friday work schedule with minimal travel.
Opportunity to work on advanced AI and cloud-native technologies.
Full Job Description
A Software Engineer is needed to design, develop, and maintain modern software applications and services. The engineer will work within a cross-functional team to build scalable cloud-native applications, microservices, and AI-enabled systems supporting both internal and external products. The role involves collaborating with software development, cybersecurity, and test engineering teams to design, implement, document, and deploy high-quality software solutions.
Overview
Location
US-Remote or Marlton, NJ area
Job Title
Software Engineer
Salary
Commensurate with industry position, depending on experience
Shift
Typical: Monday through Friday 9am to 5pm
Travel
Less than 5%
Position Responsibilities
Design, develop, test, and deploy scalable applications, APIs, and microservices using modern software engineering practices.
Build and integrate AI-enabled capabilities into applications, including machine learning models, LLM integrations, and data-driven services.
Participate in architecture and design reviews to ensure solutions meet scalability, security, and performance requirements.
Develop cloud-native services and containerized applications deployed using Docker and Kubernetes.
Integrate AI models, data pipelines, and inference services into production systems.
Collaborate with cross-functional teams including DevOps, cybersecurity, QA, and product stakeholders.
Develop and maintain technical documentation including system architecture diagrams, API specifications, and AI model documentation.
Maintain code repositories using modern version control and CI/CD pipelines.
Apply secure coding practices and support DevSecOps workflows.
Utilize AI-assisted development tools (e.g., LLM coding assistants, code analysis tools) to enhance productivity and code quality.
Monitor and troubleshoot applications in distributed environments using logging, observability, and telemetry tools.
Minimum Security Clearance
Must be eligible and pass security screening to obtain DoD Top Secret
Required Qualifications and Skills
Strong proficiency in software design, development, and debugging.
Experience with modern programming languages such as Java, Python, or similar backend technologies.
Experience with Spring Boot, REST APIs, and microservices architectures.
Experience with AI/ML technologies, including machine learning frameworks (TensorFlow, PyTorch) or modern AI integration tools.
Experience integrating AI services, LLM APIs, or intelligent automation capabilities into applications.
Experience building containerized applications using Docker and Kubernetes.
Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Experience with relational databases (MySQL, MariaDB, PostgreSQL).
Understanding of CI/CD pipelines, automated testing, and DevSecOps practices.
Familiarity with the AI/ML lifecycle including data preparation, model training, evaluation, deployment, and monitoring.
Ability to analyze problems, design solutions, and work collaboratively in a team environment.
