[Hiring] Head of AI @Legends

Role Description

Lead the technical development and strategic direction of an agentic AI core for security operations.

Remote (South Africa), Industry: Cybersecurity, Working hours: Monday to Friday 8-5 pm (UK working hours).

Salary: Market Related

The purpose of this role is to own the intelligence layer that differentiates the company and lead the strategic evolution of the AI from a prototype into a scalable, in-house intelligence engine. The role exists to lead the technical development, architecture, and roadmap of the agentic AI core while reporting directly to the CTO/CPO. The main focus areas involve migrating from cloud-dependent models to self-hosted open-source LLMs and ensuring the system is cost-efficient and production-ready.

Key Responsibilities

• Possess 7+ years in AI/ML engineering, with 3+ years on production LLM or agentic systems.
• Own the AI roadmap end-to-end, including planning, prioritisation, delivery, and reporting to leadership.
• Lead the strategic migration from AWS Bedrock to a self-hosted open-source LLM like Llama or Mistral.
• Extend and maintain the LangGraph-based multi-agent pipeline and the Strands cognitive layer.
• Provide technical direction and mentorship to existing data scientists and engineers.
• Implement cross-module incident correlation and behavioural anomaly detection.
• Manage LLM cost governance, token economics, and GPU infrastructure planning.
• Collaborate with backend engineers on FastAPI integration, AWS infrastructure, and GitLab CI/CD.

Qualifications

• 7+ years in AI/ML engineering, with 3+ years on production LLM or agentic systems.
• Demonstrated ownership of an AI system end-to-end from architecture to production.
• Strong Python skills and experience with LangGraph, LangChain, or equivalent frameworks.
• Deep understanding of hybrid LLM architectures and when to use deterministic code vs. LLM inference.
• Experience with open-source LLM deployment, fine-tuning, RAG, and vector databases like Qdrant.
• Proficiency with AWS services, including Bedrock, Lambda, EC2, S3, and DynamoDB.
• Cybersecurity background and familiarity with Splunk, Cribl, or MITRE ATT&CK.
• Data analytics experience in anomaly detection, clustering, or user risk scoring.