Principal AI Engineer (6 Months Contract)

Role Summary We are seeking a hands-on Principal AI Engineer to design, build and help productionise agentic AI systems for cybersecurity use cases. This is an AI engineering role applied to cybersecurity. The role will define and build the agentic AI harness, control plane, model evaluation framework, AI-to-system interface layer, memory and knowledge architecture, guardrails, observability model and production standards needed to deploy AI agents safely across cyber functions. Required Experience Strong hands-on experience building production-grade LLM, agentic AI, ML, automation or platform systems. Deep understanding of agent architecture, orchestration frameworks, tool calling, memory design, RAG, model routing and multi-agent workflows. Experience with frontier models, open-source models or both, including evaluation, benchmarking and model comparison. Strong software engineering background, including Python, APIs, backend services, cloud platforms, containers, CI/CD, authentication, logging and production observability. Experience integrating AI systems with enterprise APIs, identity systems, data platforms, workflow engines, ticketing systems, code repositories and operational tools. Prior experience operating or supporting production systems, including monitoring, alerting, incident response, rollback, release management, access control, cost management and post-incident review. Practical understanding of production failure modes such as model drift, prompt regressions, broken tool calls, API failures, retrieval errors, permission issues, latency problems, data quality gaps, cost spikes and unsafe outputs. Practical understanding of AI safety risks, including hallucination, prompt injection, insecure tool use, excessive agency, sensitive data leakage, memory poisoning, adversarial manipulation and unsafe autonomous behaviour. Experience designing human-in-the-loop workflows for high-risk, regulated or security-sensitive environments. Ability to design fo…