Software Engineer

GALT•San Diego, CA

17d•Onsite

About The Position

GALT Aerospace is seeking a full-time, salaried Software Engineer II or III to design, develop, integrate, and sustain software for complex aerospace and defense systems. This role involves full-stack software development, distributed systems, hardware/software integration, automation, and deployment into secure and disconnected environments. Contribute to the full software development lifecycle, including requirements analysis, architecture and design, implementation, integration, testing, deployment, and sustainment.

Requirements

Bachelor's degree in in Computer Science, Software Engineering, Computer Engineering, or a related STEM field.
5+ years of professional software development experience.
Experience developing full-stack or distributed software applications using technologies such as: Python or similar programming languages js or similar modern front-end frameworks RESTful APIs and service-based architectures Bash and/or PowerShell scripting
Knowledge of Linux administration (RHEL preferred)
Strong software development fundamentals, including data structures, debugging, software design, and maintainable coding practices.
Ability to independently own and drive software features from requirements through implementation, integration, and testing.
Experience developing and troubleshooting software on Linux systems; Red Hat Enterprise Linux experience is preferred.
Understanding of distributed application communication concepts, including RPC and publish/subscribe messaging.
Experience integrating software with external systems, devices, or hardware interfaces.
Experience with relational and/or NoSQL databases and data stores.
Experience developing and deploying containerized applications using Podman or other OCI-compatible container technologies.
Proficiency with Git and standard version-control practices.
Experience with Ansible or similar configuration and deployment automation technologies.
Strong debugging and troubleshooting skills across software and system-level components.
U.S. Citizenship and the ability to obtain and maintain a DoD security clearance.

Nice To Haves

Hands-on experience using large language models (LLMs), generative AI, and AI agents as part of software development, engineering, or automation workflows .
Experience developing or integrating AI agents and agentic workflows, particularly agents capable of interacting with tools, APIs, files, databases, source-code repositories, or other resources to perform multi-step engineering tasks.
Experience with AI tool/function calling, Model Context Protocol (MCP), retrieval-augmented generation (RAG), or similar approaches for connecting AI models with external systems and engineering data.
Familiarity with local or on-premises AI infrastructure and technologies such as Ollama, Open WebUI, vLLM, Hugging Face, or similar tools.
Familiarity with local or on-premises AI infrastructure and technologies such as Ollama, Open WebUI, vLLM, Hugging Face, or similar tools.
Experience with Protocol Buffers (Protobuf) and RPC frameworks such as gRPC or similar technologies.
Experience designing or developing systems using publish/subscribe messaging, event-driven architectures, message brokers, or similar distributed communication patterns.
Experience developing and troubleshooting software interfaces with external hardware, including serial and other device communication protocols.
Experience deploying, operating, or maintaining software in disconnected or air-gapped environments, including offline dependency and package management.
Experience developing, deploying, or troubleshooting software in virtualized environments.
Networking knowledge including TCP/IP, UDP, multicast, DNS, routing, firewalls, and virtual networking.
Experience with low-level hardware/software integration, device APIs, drivers, GPIO, or Linux system interfaces.
Familiarity with CI/CD and DevOps practices and tools such as Jenkins, GitLab CI/CD, or similar platforms.
Knowledge of cybersecurity best practices, secure software development, system hardening, and vulnerability management.
Experience working within highly regulated, secure, or DoD software environments.
Active DoD security clearance or the ability to reinstate a previously held clearance.
Advanced degree or relevant technical certifications.

Responsibilities

Take ownership of and lead individual software features from requirements and design through implementation, integration, testing, and delivery.
Collaborate with other software engineers and cross-functional engineering teams to integrate features into larger systems.
Build and maintain full-stack applications, including front-end interfaces using Vue.js, APIs, and backend services primarily developed in Python.
Design, develop, and integrate distributed software services using RPC, publish/subscribe messaging, and other inter-process or network communication patterns.
Develop and integrate software interfaces using technologies such as Protocol Buffers and service-based APIs.
Integrate software with external devices and hardware using serial interfaces, network protocols, and device-specific APIs.
Integrate new features and capabilities into complex, multi-VM Systems-of-Systems deployed in secure, fully disconnected and air-gapped environments.
Develop and maintain Ansible playbooks used to configure, provision, and deploy Red Hat Enterprise Linux (RHEL) systems and Windows virtual machines.
Develop, containerize, deploy, and troubleshoot software components using Podman and OCI-compatible container technologies.
Develop and troubleshoot software running across Linux and Windows environments.
Develop, integrate, and troubleshoot software deployed across physical and virtualized environments.
Participate in code reviews, architecture discussions, technical planning, system integration activities, and internal process improvement initiatives.
Explore and implement practical uses of artificial intelligence and large language models (LLMs) to improve software development, engineering workflows, system capabilities, and automation.
Develop or integrate AI agents and agentic workflows capable of interacting with tools, APIs, software repositories, documentation, and other engineering resources.
Troubleshoot complex issues spanning application software, distributed services, operating systems, networking, virtualization, containers, and hardware interfaces.