About OPSWAT
OPSWAT is a global leader in IT, OT, and ICS critical infrastructure cybersecurity, delivering an end-to-end platform that gives public and private sector organizations and enterprises the critical advantage needed to protect their complex networks, secure their devices, and ensure compliance. Our commitment to innovative technology has earned the trust of over 1,700 organizations, governments, and institutions globally, solidifying our role in protecting the world’s critical infrastructure.
The Product: MetaDefender MFT
MetaDefender MFT is OPSWAT’s enterprise-grade Managed File Transfer solution designed to help organizations securely exchange, automate, and govern file transfers across enterprise and regulated environments. It provides:
- Secure File Exchange: A secure and scalable file transfer platform for both human and system-to-system workflows across enterprise environments.
- Threat Prevention and Compliance: Integrated security capabilities embedding OPSWAT technologies such as multiscanning, Deep CDR™ Technology, DLP, and centralized auditability directly into file transfer operations.
- Enterprise Platform Evolution: A mature and continuously evolving platform focused on reliability, automation, operational visibility, and secure enterprise integration.
As part of the MetaDefender MFT team, you will contribute to the evolution and modernization of a platform trusted by enterprise and critical infrastructure organizations worldwide.
The Position
As an AI Native .NET Engineer, you will orchestrate a fleet of AI agents to architect, build, and deploy production-grade systems, with AI agents being a core part of your daily workflow. You will build complex multi-service systems, create custom coding harnesses and test frameworks, and reverse-engineer existing systems entirely through AI workflows. Your performance will be measured by the speed of deployment and the robustness of what you ship, not the volume of your commits. You will think in terms of “how do these pieces fit together as a system” and blend product, design, and analytical thinking into your delivery.
You Will Have The Opportunity to
- Take ownership of supervisor approval workflows — designing and evolving the backend systems that route file transfers through configurable approval chains, status tracking, and policy-driven decision flows.
- Develop and maintain audit logging and compliance capabilities — building reliable and traceable event tracking for user activities and file transfer operations across the platform.
- Leverage modern AI-assisted development tools to improve engineering workflows, accelerate implementation, and support activities such as code generation, testing, documentation, and review processes while maintaining ownership and quality of delivered solutions.
- Participate in code reviews with a security-first lens, offering constructive feedback and holding the quality bar for both human-written and AI-generated code.
- Create custom coding harnesses and test frameworks for structured, repeatable AI-assisted development — giving the team reliable scaffolding that agents can operate within safely and consistently.
- Author and keep current AI context files for every service you own — machine-readable architecture docs that encode coding standards, architectural constraints, and forbidden patterns so agents produce consistent, safe, on-pattern code across the team.
- Help define and codify AI-native engineering practices for the MFT team — establishing playbooks, context file standards, and review norms the broader engineering organization can adopt.
What We Are Looking For
- AI-Native Fluency: Deep, hands-on experience integrating AI agents as core engineering tools, not add-ons — approaching every problem with an AI-native mindset. Must show real work (PRs, commit history, or portfolio) where agents drove backend velocity.
- Technical Excellence (.NET Core / C#): Strong proficiency in .NET / C# with a S.O.L.I.D understanding of programming principles, design patterns, and best practices. AI tools amplify strong fundamentals — they do not replace them.
- Mission-Focused Delivery: 3+ years experience developing scalable solutions, including familiarity with relational/document databases and modern CI/CD systems for seamless integration and delivery.
- Quality and Test Discipline: Focus on high-quality tested solutions — proficiency in unit testing with xUnit or equivalent. Uses AI agents to generate test scaffolding quickly, then validates that coverage is real and meaningful.
- Growth Mindset: Passion for continuous learning. The AI coding ecosystem evolves rapidly — new models, agents, and tooling patterns ship constantly. This role requires staying current across the landscape and actively improving team workflows as the toolchain matures.
It Would be Nice if You Had
- Agent Discipline: Writes precise, unambiguous task specifications that agents can execute without re-prompting, and treats all AI-generated code as a junior engineer’s PR — reviewing for logic, security, edge-case handling, and architectural fit before anything ships.
- Async programming (.NET): Knowledge of asynchronous .NET patterns — async/await, TPL — with experience validating AI-generated async code for thread-safety in high-throughput scenarios.
- Containerization: Familiarity with Docker — able to run services locally in containers, read a Dockerfile, and understand how containerized deployments differ from traditional installs.
- Security review of AI-generated code: Security-first instincts for reviewing AI-generated code: spotting injection risks, insecure defaults, missing input validation, and privilege escalation vectors in file-handling and authentication code.
- AI context file authoring: Experience authoring AI context files (e.g., CLAUDE.md, .cursorrules, or equivalent) that encode architecture decisions and forbidden patterns for consistent, safe AI output across a team.
- AI in CI/CD pipelines: Familiarity with running AI agents inside CI/CD pipelines — auto-fixing lint, generating missing tests, or running safe migrations as pipeline steps.
- Personal projects: A home or personal project that demonstrates commitment to programming — including any AI-tooled projects that show how you work with agents.