In this role, youll lead a team of top-tier software engineers, owning the architecture, scalability, and seamless integration of AI-driven capabilities into a high-performance, real-time security platform. You'll play a key role in transforming advanced AI technologies into impactful, production-ready solutions.
Our group combines the speed and creativity of a startup with the backing of a global cybersecurity leader. If you're passionate about solving complex technical problems, leading exceptional talent, and building innovative AI-powered systems with real-world impact we want to hear from you.
Key Responsibilities
Lead, mentor, and grow a team of software engineers, fostering a high-performing culture and supporting recruitment, onboarding, and career development
Drive the design, architecture, and technical direction of the AI-powered product, ensuring it meets performance, scalability, and integration goals
Work closely with data scientists, product managers, and engineering teams to align on strategy, execution, and delivery
Ensure robust, scalable, and reliable deployment in production
Stay on top of emerging AI technologies and best practices, evaluating and integrating advancements to keep the product and team at the cutting edge
Requirements: 5+ years of hands-on software engineering experience, including at least 2 years in a technical leadership role within AI or data-intensive product teams
Proficiency in Python, with strong experience designing, building, and operating scalable backend systems and cloud-native applications in production environments
Strong leadership and execution skills, with a demonstrated ability to mentor engineers, lead cross-functional initiatives, and align technical execution with product and business objectives
Experience developing and maintaining robust data pipelines and backend services that integrate with data science workflows and support AI-powered product features
Practical experience with GenAI frameworks (e.g., OpenAI APIs, LangChain, vector databases), and a solid understanding of integrating LLMs into real-world systems using RAG, agent-based architectures, and structured data
Background in cybersecurity or network infrastructure strong advantage
BSc in Computer Science or a related field; MSc advantage
This position is open to all candidates.