Red Team Security Engineer

Key Responsibilities

• Plan and execute red team engagements, penetration tests and adversary simulations against our platforms, products and corporate environment. 
• Identify, exploit and document vulnerabilities across web applications, APIs, cloud infrastructure, identity systems and AI/LLM-based services. 
• Develop realistic attack scenarios — initial access, privilege escalation, lateral movement, data exfiltration — mapped to frameworks such as MITRE ATT&CK. 
• Build and maintain custom tooling, exploits and automation where off-the-shelf tools fall short. 
• Leverage AI pen testing tooling and frameworks as a force amplifier within your role. 

• Active, hands-on use of AI-powered offensive security tooling as a core part of your workflow — leveraging LLMs and agentic assistants to accelerate reconnaissance, exploit development, code review, payload generation and report writing. 
• Familiarity with emerging AI red-team frameworks and platforms — e.g. PyRIT, Garak, Promptfoo, NVIDIA Aegis, Microsoft Counterfit, HackerOne / Bugcrowd AI testing toolkits, or equivalent — and a practical sense of when to use which. 
• Experience building or extending automated AI red-team harnesses: prompt-injection test suites, jailbreak corpora, tool-abuse scenarios, multi-turn attack agents, and regression eval sets for LLM and agentic systems. 
• Pragmatic judgement on the limits and risks of AI-assisted offensive work — hallucinated findings, false confidence, data leakage into third-party models — and the discipline to validate AI output before acting on it. 
• Curiosity to keep pace with a fast-moving space: new models, new attack techniques, new defensive controls — and a willingness to bring those learnings back into the team. 

• Probe LLM-powered and agentic systems for prompt injection, jailbreaks, tool/function-call abuse, context leakage, insecure output handling and supply-chain risks. 
• Test RAG pipelines, knowledge bases and integrations for data exfiltration, poisoning and unauthorised access paths. 
• Contribute to internal threat models for agentic architectures and help shape secure-by-default patterns for multi-agent and tool-using systems. 
• Stay close to evolving standards and guidance (e.g. OWASP Top 10 for LLMs, NIST AI RMF, emerging agent interoperability protocols). 

• Perform deep-dive security testing of cloud workloads across AWS, Azure and/or GCP — IAM, network, container, serverless and data-layer concerns. 
• Review CI/CD pipelines, IaC (Terraform, CloudFormation, Bicep) and Kubernetes deployments for misconfigurations and exploitable weaknesses. 
• Conduct source-assisted ("grey-box") testing — reading code to find logic flaws, authZ gaps and unsafe integrations. 

• Triage findings, assign realistic severity, and write clear, reproducible reports with concrete remediation guidance. 
• Partner with engineering teams to validate fixes, advise on secure design and pair on hardening work — not just throw findings over the wall. 
• Drive continuous improvement of detection coverage by working with the blue team / SOC on purple-team exercises. 

• Build automation that turns one-off tests into repeatable, scheduled checks — exposure scanning, attack-path analysis, agent red-teaming harnesses. 
• Integrate offensive testing into the SDLC: SAST/DAST/IAST, dependency scanning, secrets detection, container and IaC scanning. 
• Treat evaluation and regression of security controls as a first-class deliverable — measured, not assumed. 

• Work alongside the Head of Information Security, AI Ethics leads, platform engineering and product teams to embed security early. 
• Produce clear design reviews, threat models, runbooks and post-engagement reports for both technical and executive audiences. 
• Operate within strict rules of engagement, with care for production stability, customer data and legal/regulatory obligations. 

Skills Knowledge and Expertise

• Demonstrable hands-on experience in offensive security — penetration testing, red teaming, or adversary simulation — against modern web, API and cloud-based systems. 
• Strong understanding of common vulnerability classes (OWASP Top 10, authZ flaws, SSRF, deserialisation, injection, cryptographic misuse) and how to chain them into real impact. 
• Solid grasp of cloud security in at least one major provider (AWS, Azure or GCP): IAM, networking, key management, container and serverless services, common misconfigurations and attack paths. 
• Practical understanding of AI/LLM systems — how they work, where they fail, and the new risks they introduce (prompt injection, jailbreaks, insecure tool use, training/RAG data exposure). 
• Coding capability in at least one of Python, Go, JavaScript/TypeScript or similar — comfortable writing exploits, tooling and automation, not just running other people's tools. 
• Confidence with offensive tooling — Burp Suite, nmap, Nuclei, BloodHound, Metasploit, custom scripts — and the judgement to know when to build vs. buy. 
• Familiarity with CI/CD, containers and IaC (Docker, Kubernetes, Terraform or equivalent) and how to attack and defend them. 
• An evaluation mindset: you measure security posture with reproducible tests, metrics and evidence — not gut feel. 
• Comfort with agentic development workflows — using AI coding assistants and AI co-work / pair-development models (Claude Code, Copilot, Cursor or equivalent) as part of your day-to-day delivery. 
• Clear written and verbal communication in English: able to brief engineers, executives and (where relevant) customers on findings and risk. 
• A strong ethical compass and discipline around scope, rules of engagement, evidence handling and responsible disclosure. 

• Industry certifications such as OSCP, OSEP, OSWE, CRTO, CRTP, GPEN, GXPN, GCPN, AWS/Azure/GCP security specialties or equivalent. 
• Experience red-teaming or evaluating agentic AI / LLM systems in production — prompt injection campaigns, tool-abuse testing, multi-agent attack scenarios, AI red-team frameworks. 
• Exposure to purple teaming and detection engineering: working with SOC/SIEM (e.g. Sentinel, Splunk, Defender XDR) to improve detections from offensive findings. 
• Experience with identity attacks across Entra ID / Azure AD, Active Directory, OAuth/OIDC and federated environments. 
• Source-code review skills and threat modelling experience (STRIDE, attack trees, MITRE ATLAS for AI). 
• Familiarity with regulatory and standards contexts relevant to enterprise customers — ISO 27001, SOC 2, PCI DSS, GDPR, POPIA. 
• Experience contributing to or running bug bounty programmes, CTFs, or open-source security tooling. 
• Awareness of emerging agent interoperability and security standards (e.g. MCP, A2A) and their attack surfaces. 

• Prior experience in a SaaS, cloud platform or AI/ML company where production systems were the target of testing — useful context, but not required. 
• Public research, conference talks, CVEs, or community contributions in offensive security or AI security. 

Benefits

• Remote/Flexible work
• Discovery Medical Aid  
• Connectivity Allowance
• 15 days paid holiday a year- (this includes three Sabio days)
• Momentum EAP