Senior Data Scientist/Engineer (Cybersecurity)

TL;DR

Senior Data Scientist/Engineer (AI/ML): Designing and deploying production machine learning and AI systems for cybersecurity platforms with an accent on LLM integration and agentic AI capabilities. Focus on building LLM evaluation frameworks and performing rigorous cost-benefit analysis for AI architectural decisions.

Location: Primarily based in Belfast, UK; UK/EMEA remote or hybrid applicants are considered, with at least quarterly travel to Belfast expected.

Company

hirify.global provides application security solutions (SAST, SCA, and DAST) to help organizations minimize risks and maximize speed in DevSecOps.

What you will do

• Design, develop, and maintain production-ready ML and AI systems with clear evaluation criteria and operational handovers.
• Lead the integration of LLM and agentic AI capabilities, including prompt engineering, RAG, and agent orchestration.
• Design and own LLM evaluation frameworks, defining metrics and building offline/online evaluation pipelines.
• Conduct cost-benefit analyses on AI/ML decisions, weighing inference costs, latency, and accuracy against business value.
• Collaborate with R&D and Product Engineering to embed AI capabilities into existing workflows.
• Mentor team members and the wider organization on emerging ML/AI engineering practices.

Requirements

• 5+ years of hands-on experience in data science or ML engineering with demonstrable delivery of production systems.
• Strong software engineering proficiency to design and deliver modules from scratch.
• Experience deploying ML/AI models in production on cloud infrastructure (AWS, Azure, or GCP) and/or Kubernetes.
• Proficiency with PyTorch, scikit-learn, HuggingFace, and experiment tracking tools like MLflow or W&B.
• Practical experience in LLM evaluation, RAG pipelines, and agentic AI patterns (LangChain, LangGraph).
• Expertise in scientific Python (pandas, numpy, scipy) and Jupyter.

Nice to have

• Degree in Computer Science, AI, Mathematics, Physics, or a related field.
• Familiarity with cybersecurity concepts and software supply chain risk.
• Experience with MLOps tooling (Airflow, DBT, Databricks) or Data Mesh concepts.
• Skill in enterprise data visualization using Power BI, Grafana, or Snowflake.
• Comfort in Linux/CLI environments and experience with Git and CI/CD.

Culture & Benefits

• A values-driven environment emphasizing Trust, Collaboration, Results, and Curiosity.
• Opportunity to work at the intersection of cybersecurity and data intelligence.
• Conference and collaboration opportunities commensurate with professional impact.
• Commitment to being an equal opportunity employer with inclusive hiring practices.