AI-Native Software Engineer - MD Core
About this role
Engineers on the MetaDefender Core team shape the architecture of a high-performance file security platform while orchestrating a fleet of AI agents to build code, tests, and documentation in parallel. Daily responsibilities include contributing to features end-to-end, embedding AI tools into the standard engineering workflow, and verifying the correctness of all generated output before deployment. The team builds core security infrastructure deployed across cloud, containerized, on-premises, and air-gapped environments.
OPSWAT created this role to scale development capacity through an AI-native operating model where developers act as system architects and technical reviewers. Ideal candidates possess a strong foundation in object-oriented programming alongside hands-on experience using AI coding assistants for real-world software delivery. Professionals who thrive here enjoy designing complex systems, establishing development guardrails, and taking ownership of software quality across multiple operating systems.
What you will do
- Contribute to features end to end by clarifying requirements, participating in design discussions, implementing, testing, debugging, and helping ship functionality.
- Utilize AI tools like Claude Code and GitHub Copilot daily to accelerate implementation, testing, debugging, and documentation while reviewing all generated output.
- Improve the team's AI-assisted workflows by refining agent configurations, prompt templates, project rules, MCP integrations, and safety guardrails.
- Write and enhance tests and quality checks that verify intended behavior, catch regressions, and ensure AI-generated code meets production standards.
- Develop advanced debugging skills to investigate complex issues that resist automation, including bug reproduction, log analysis, and concurrency diagnostics.
- Prototype and evaluate AI-powered product capabilities such as LLM-assisted analysis, automated triage, and support for new integrations.
- Collaborate directly with product management and quality assurance teams to understand requirements and make technical trade-offs.
What you need
- Hold a bachelor's degree in a technical field or possess equivalent practical experience.
- Demonstrate at least one year of professional experience with a clear track record of feature ownership.
- Show a solid understanding of object-oriented programming, SOLID principles, and common design patterns.
- Bring practical experience with multi-threaded programming and system design.
- Possess strong coding and debugging skills, including comfort navigating large codebases and diagnosing issues across operating system boundaries.
- Demonstrate an AI-native development mindset with hands-on experience using AI coding assistants and agentic tools in production environments.
- Possess working knowledge of LLM fundamentals including prompt design, tool calling, output evaluation, and data privacy considerations.
- Exhibit strong verbal and written communication skills to articulate technical concepts clearly.
Nice to have
- A real track record shipping and maintaining production systems in any tech stack
- Hands-on Rust or C++ experience
- Experience building AI agents or agentic pipelines, including tool contracts and multi-step orchestration
- Performance profiling and networking knowledge across the OSI model
- Familiarity with cybersecurity concepts, security products, and database management systems like SQLite or PostgreSQL
Skills and tech stack
Questions candidates ask
What is the remote work policy for this position?
The job posting indicates an onsite requirement with the location specified as Ho Chi Minh City, Vietnam, under the label #LI-Onsite.
What AI tools will I use in my daily workflow?
Engineers work with tools such as Claude Code and GitHub Copilot to accelerate implementation, testing, debugging, and documentation. You will also help improve agent configurations, prompt templates, and MCP integrations.
What operating environments will I work with?
You will develop across Windows and Linux environments while gaining exposure to cloud, containerized, on-premises, and air-gapped deployments.