AI Engineer (Security)

Capital Com Australia limited; Województwo mazowieckie; On-site; PLN 60,000 - 90,000; Full time

Benefits offered by this job

Competitive Salary

Work-Life Harmony

Generous Time Off

Employee Referral Program

Comprehensive Health & Pension Benefits

Workation Wonderland

Volunteer Days

Job summary

Capital Com Australia limited is seeking an AI Security Engineer to enhance the security of its AI-driven systems, including LLM-based applications. The role involves designing security controls, mitigating AI-specific threats, and ensuring compliance with regulations. Candidates should have 3–5+ years of relevant experience, strong cloud platform skills, and the ability to work cross-functionally. Benefits include competitive salary, work-life balance, generous leave, and health benefits.

Qualifications

• 3–5+ years in software engineering, ML engineering, or application security.
• Hands-on experience with AI/ML systems (LLMs, NLP models).
• Experience working with Claude Code.
• Strong understanding of cloud platforms like AWS, Azure, or GCP.

Responsibilities

• Design and implement security controls for AI/ML systems.
• Identify and mitigate AI-specific threats.
• Integrate AI security checks into CI/CD pipelines.
• Conduct AI risk assessments and ensure compliance with regulations.

Skills

Software engineering

ML engineering

Application security

Python proficiency

Cloud platforms (AWS, Azure, GCP)

API security

Docker

Kubernetes

AI-specific security risks

Threat modeling

Job description

We are looking for an AI Security Engineer to secure our AI-driven systems, including LLM-based applications, machine learning models, and AI-enabled automation tools. This role will focus on identifying, assessing, and mitigating security risks across the AI lifecycle — from model development and training to deployment and runtime monitoring. The ideal candidate combines strong security engineering experience with a deep understanding of machine learning systems and emerging AI-specific threats (e.g., prompt injection, model poisoning, data leakage, adversarial attacks).

Key Responsibilities

AI/ML Security Architecture

• Design and implement security controls for AI/ML systems across development, training, and production.
• Secure LLM integrations, RAG pipelines, and AI APIs.
• Conduct threat modeling for AI systems and data pipelines.
• Define secure-by-design patterns for AI-powered features.

AI Threat Detection & Mitigation

• Identify and mitigate AI-specific threats: prompt injection and jailbreak techniques, model poisoning and data contamination, adversarial attacks, training data leakage, insecure model serialization, excessive permissions in AI agents.
• Develop guardrails, content filters, and output validation mechanisms.
• Implement monitoring for anomalous AI behavior.

Secure Development & DevSecOps

• Integrate AI security checks into CI/CD pipelines.
• Perform security reviews of ML code and AI-related infrastructure.
• Secure model registries and artifact storage.
• Collaborate with other engineers and platform teams to enforce security standards.

Data Protection & Compliance

• Ensure AI systems comply with GDPR, data privacy regulations, financial industry regulatory requirements, implement controls for sensitive data used in training and inference, and perform AI risk assessments aligned with internal risk methodology.

Governance & Policy

• Contribute to AI security standards and internal policies.
• Define AI risk classification and control frameworks.
• Support security reviews for new AI initiatives and tools.

Required Qualifications

• 3–5+ years in software engineering, ML engineering, or application security.
• Hands‑on experience with AI/ML systems — LLMs, NLP models, or similar.
• Python proficiency for automation and scripting.
• Experience working with Claude Code.
• Strong understanding of cloud platforms: AWS, Azure, or GCP.
• Experience with API security, Docker, Kubernetes.
• Knowledge of AI‑specific security risks and mitigations.
• Experience conducting threat modeling and risk assessments.

Preferred Qualifications

• Familiarity with RAG architectures, vector databases, ML pipelines (MLflow, Kubeflow, SageMaker).
• Experience in fintech or regulated environments.
• Knowledge of AI governance frameworks (EU AI Act, NIST AI RMF, ISO/IEC 42001).
• Experience with AI red teaming.
• Background in cybersecurity or application security (OWASP, Secure SDLC).

Soft Skills

• Strong analytical and problem‑solving skills.
• Ability to translate technical risk into business impact.
• Ability to explain AI security risks and mitigations to non-security teams.
• Cross‑functional collaboration with ML, data, and product teams.
• Clear documentation and communication skills.

Benefits

• Competitive Salary: Your skills and talents will be rewarded with a salary that makes you feel valued and motivated.
• Work-Life Harmony: Join a company that genuinely cares about you — your life outside of work matters as much as your time on the clock.
• Generous Time Off: Our annual leave policy lets you recharge and enjoy life outside of work without worry.
• Employee Referral Program: Bring your talented friends on board and get rewarded for growing our awesome team.
• Comprehensive Health & Pension Benefits: From medical insurance to pension plans, we’ve got your back, plus location‑specific benefits and perks.
• Workation Wonderland: Live your digital nomad dreams with 30 extra days to work remotely from anywhere in the world (some restrictions apply).
• Volunteer Days: Take two additional paid days each year to support causes you care about and give back to the community.