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This opportunity is suited to experienced AI/ML engineers who enjoy contributing to early-stage technology ventures and helping shape foundational systems from the ground up.

Our client is an emerging cybersecurity technology company developing advanced AI-driven infrastructure to strengthen cyber risk intelligence, compliance automation, and operational resilience for highly regulated industries.

They are seeking a Senior AI/ML Engineer (Fractional) to support the development of next-generation AI capabilities within their platform.

This engagement is designed for senior engineers who are comfortable working within early-stage environments where technical contributors help build long-term capability alongside company growth.

About the Opportunity

This role is structured as a fractional technical engagement (approximately 8 hours per week) and will work alongside a small team of engineers and domain specialists.

You will contribute to the design and implementation of advanced AI systems capable of interpreting large volumes of security data, generating contextual intelligence, and supporting automated risk analysis.

The focus is on building production-ready AI infrastructure that can scale with the platform's evolving capabilities.

What You'll Be Building

Advanced NLP Systems

Develop natural language processing models capable of extracting structured insight from unstructured documents, threat intelligence feeds, and security reports.

LLM / Retrieval Systems

Build retrieval-augmented intelligence systems that generate contextual security insights and assist with automated risk analysis.

Knowledge Graph Architecture

Design dynamic knowledge graph structures that map relationships among assets, vulnerabilities, and regulatory frameworks.

Real-Time AI Pipelines

Develop scalable ML pipelines that process security data streams and deliver actionable insights.

Key Responsibilities

AI Architecture & Engineering

• Designing and deploying production-grade NLP models for security intelligence analysis
• Developing knowledge graph systems connecting assets, vulnerabilities, and compliance frameworks
• Building LLM-based intelligence capabilities to support automated cyber risk insights

Technical Delivery

• Implementing robust MLOps pipelines to support model lifecycle management
• Optimising model performance for real-time or near-real-time security analysis
• Collaborating with domain specialists to translate cybersecurity concepts into machine learning models

Strategic Contribution

• Contributing to the technical roadmap for AI capabilities within the platform
• Researching emerging AI techniques relevant to cybersecurity and risk analysis
• Supporting architecture decisions that enable long-term scalability

Who This Opportunity Is For

You are likely to be a strong fit if you:

• Hold an advanced degree in Computer Science, AI/ML, Mathematics, or a related technical field
• Have 5+ years of experience building production AI/ML systems
• Have strong expertise in NLP frameworks (e.g., spaCy, Hugging Face, OpenAI APIs)
• Have experience working with knowledge graph technologies (e.g., Neo4j, Neptune, or similar)
• Have hands-on experience with LLM/RAG architectures
• Have strong programming skills in Python with frameworks such as PyTorch or TensorFlow
• Are comfortable working within cloud environments (AWS, Azure, or GCP)

• Experience working with cybersecurity data or threat intelligence

• Familiarity with frameworks such as NIST, ISO 27001, SOC 2, DORA, or OWASP
• Experience building ML systems within regulated industries

Engagement Structure

This role is structured as a fractional technical engagement (approximately 8 hours per week) for experienced engineers interested in contributing to the technical foundation and development of an emerging cybersecurity technology platform at an early stage.

Participation is aligned with the company's current growth phase and is structured around long-term strategic involvement and shared upside as the platform scales.

As the organisation progresses through future growth milestones, there will be opportunities for the engagement structure to develop alongside the company's trajectory.

This opportunity is well-suited to engineers who enjoy solving complex technical problems and contributing to foundational systems in emerging technology environments.