Blackwall is building the next generation of AI-powered security infrastructure to protect the web from automated threats. We combine behavioural intelligence, real-time protection, and performance optimization to safeguard hosting environments and drive operational efficiency.
We’re now hiring an AI Engineer to join our growing team and work closely with our Head of AI. You’ll help us bring intelligence to two distinct AI initiatives:
- Embedding AI capabilities into our Web Application Firewall (WAF), and
- Powering behavioural analysis across the Blackwall server to detect and mitigate bot-driven threats.
This is a hands-on, cross-functional role for someone who thrives at the intersection of data science, software engineering, and security infrastructure.
Role Details
- Engagement type: Full-time (contract basis)
- Location: Remote (within Europe)
- Compensation: Paid position; rate depends on experience and location
Tasks
- Collaborate with the Head of AI, product managers, and engineers to identify and deliver AI-driven security features.
- Engineer and deploy ML models (e.g., LLMs, classifiers, anomaly detectors) into real-time systems like our WAF and behavioral analytics engine.
- Build robust, low-latency ML pipelines using Python, C++, and SQL – ensuring performance, scalability, and maintainability.
- Apply adversarial learning and behavior modeling to differentiate between bots and human traffic under live traffic conditions.
- Design and implement workflows that enhance data quality, latency, and decision reliability across production services.
- Monitor, evaluate, and optimize deployed models, ensuring continuous learning and adaptation to emerging threats.
- Present results and trade-offs in a clear, structured way to both technical and non-technical stakeholders.
- Contribute to Blackwall’s AI engineering practices by mentoring peers, conducting code reviews, and improving tooling.
Requirements
- 3+ years of hands-on experience as an ML/AI engineer working on production systems, ideally in real-time or high-throughput environments.
- Strong foundation in software engineering practices: version control, CI/CD, containerization, code testing, performance tuning.
- Proficient in Python and SQL, with solid exposure to C++ or other systems-level languages.
- Deep knowledge of ML models and deployment strategies – especially classification, anomaly detection, and behavioral modeling.
- Experience working with LLMs or generative AI frameworks, including fine-tuning and serving.
- Proven ability to translate ML research into scalable, reliable software systems.
- Degree in Computer Science, Engineering, Mathematics, or a related technical field; MSc or PhD preferred.
- Experience working cross-function