Director of Engineering (AI)

Our client is a global leader in cybersecurity for IT, OT, and ICS critical infrastructure. Their end-to-end platform gives enterprises and public sector organizations the critical advantage they need to protect complex networks, secure devices, and meet compliance requirements.

Over the past 20 years, a consistent commitment to innovative technology has earned the trust of more than 1,700 organizations, governments, and institutions worldwide - cementing the company's role in protecting the world's critical infrastructure and securing our way of life.

On their behalf, we are looking for a Director of Engineering ready to contribute to that mission.

This is a hands-on, technically-centric leadership role - not a pure people-management position - with full accountability for the engineering of MetaDefender Managed File Transfer: architecture, delivery, quality, and the teams that build it. You will lead engineering across multiple deployment form factors - from air-gapped and cross-domain environments to internet-connected and native-cloud deployments - operating with the rigor of a principal engineer and the clarity of an executive.

You are an AI-native engineering leader. You have personally orchestrated fleets of AI agents to architect, build, test, and ship production systems, and you have launched and released real products through a full AI-powered software development lifecycle (SDLC) - from specification and code generation to automated testing, review, and deployment. Product Management defines what to ship; you define how to build it. You own the end-to-end delivery of the roadmap Product Management sets, hold the delivery bar, and build a high-performance culture that the rest of our client's engineering portfolio will look to as a model for AI-native development. You report to the VP, Products, and lead a distributed team across Romania, Vietnam, and Hungary, while the role itself can be based anywhere, with a preference for the UK, USA.

Your Responsibilies:

• Lead as an AI-first effort: make AI agents a first-class part of how the team works - orchestrating agents to create specs, generate code and tests, verify results, and run reviews - while ensuring humans own and validate every line that ships. Treat automation and intelligence as the default, not the exception.
• Stay hands-on: remain directly in the codebase - setting architecture patterns, writing and reviewing critical code, prototyping, and unblocking hard technical problems. You lead by doing, not only by delegating.
• Own end-to-end delivery of the roadmap: take full ownership of delivering the product roadmap set by Product Management - turning the “what to ship” into the “how to build,” and owning execution sequencing, technical risk, quality, security, and release across every deployment form factor.
• Set technical direction (the “how”): drive the architecture and technology choices that underpin a product serving high-assurance environments at scale. Hold a strong engineering point of view and be willing to defend it.
• Build and lead a high-performance team: recruit, develop, and retain top engineers and their leads across Romania, Vietnam, and Hungary; create clear career paths and norms for code quality and review; and build a culture where strong engineers want to stay and grow.
• Drive performance-based management: set clear, measurable expectations and run a rigorous, fair performance culture - recognizing and accelerating top performers, raising the bar continuously, and addressing underperformance decisively by coaching where there is a path and upgrading or exiting the role where there is not.
• Hold a security-first quality bar: champion code review with a security lens for both human-written and AI-generated code, catching injection risks, insecure defaults, missing validation, and privilege-escalation vectors in file-handling and authentication paths before they ship.
• Raise engineering velocity: continuously improve how the team works - CI/CD pipelines, AI-assisted development workflows, incident response, and operational maturity - so the team ships faster and more reliably over time.
• Codify AI-native practices for the portfolio: establish the playbooks, AI context files, coding harnesses, test frameworks, and review norms developed on this product so other product teams can adopt them.
• Partner cross-functionally: work shoulder-to-shoulder with the VP, Products, plus Product Management, Design, and security leaders - turning the product roadmap (the what) into engineering execution (the how), committing to scope and timelines, and pushing back clearly when trade-offs require it.

Requirements

• Full agentic development experience (required): you have personally run a full agentic, AI-powered SDLC end to end - and have done so in B2B and high-security enterprise environments where compliance, data sensitivity, and assurance requirements are non-negotiable. You can show real work (PRs, commit history, shipped products, or a portfolio) where agentic workflows drove delivery - not slideware about AI.
• A product launched via a full AI-powered SDLC: demonstrable experience taking a product from spec to release using an end-to-end AI-assisted lifecycle (spec generation, code/test generation, automated verification, AI-assisted review, and CI/CD), with you accountable for the outcome.
• Proven engineering leadership: 8+ years of software engineering experience and 3+ years leading engineering teams (including managing managers/leads) through complex product delivery at scale. You can point to the decisions you made and why.
• Performance-based leadership: a track record of building high-performing teams through rigorous, fair performance management - promoting excellence, making timely talent decisions, and reducing or replacing low performers when needed.
• Deep technical excellence: strong, current software engineering fundamentals - solid command of design patterns, SOLID principles, and modern architecture. You can evaluate AI-assisted code with the same rigor as human-authored code. AI tools amplify strong fundamentals; they do not replace them.
• Scalable systems experience: a proven history building scalable, distributed solutions - including relational/document databases, cloud-native services, and modern CI/CD systems.
• Quality and test discipline: a high bar for tested, maintainable code; you use AI to accelerate test scaffolding, then validate that coverage is real and meaningful.
• Distributed-team leadership: demonstrated ability to lead and align engineers across countries and time zones, building trust, clarity, and accountability in a remote/hybrid, multi-country setup.
• Talent magnet and clear communicator: you identify strong engineers, make a compelling case for why they should join, and create an environment where they do their best work - and you communicate technical decisions to non-technical stakeholders without oversimplifying.
• Security-conscious by default: operating in critical infrastructure markets means security is never an afterthought; you hold the team to a security-first bar on design, code review, and incident response.

Nice To Have:

• Domain familiarity: experience with managed file transfer, secure content delivery, data security, or critical infrastructure markets - you understand the trade-offs customers in this space make.
• .NET / C# ecosystem: hands-on or managerial experience with .NET Core / C# - enough to evaluate architectural decisions, review PRs credibly, and hire well for the stack.
• Cloud-native and containers: experience leading the design or operation of cloud-native SaaS platforms - Docker, Kubernetes, and AWS/Azure/GCP - including using AI agents to script infrastructure and deployment automation.
• AI context-file authoring: experience writing 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 running AI agents inside pipelines - auto-fixing lint, generating missing tests, or running safe migrations as pipeline steps - not as experiments, but as how the team actually works.
• International team experience: a track record of building and maintaining engineering culture and delivery quality across multiple countries and time zones.
• Async and high-throughput systems: experience validating concurrency and thread-safety in high-throughput services.

Benefits

• Stable, growing international company background with an exceptional customer group
• Opportunity to improve your professional skills
• The newest technology environment
• Language course and opportunity for active recreation - kettlebell, football and office massage
• Attractive working environment - nice office full of accessories (fruits every day, coffee, breakfast, tea etc.)
• Regular team events and Happy Hour activities