AI Security Engineer for Newra, Part of Accenture
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AI Security Engineer for Newra, Part of Accenture
Location
Athens, Central Athens, Greece
Experience
Mid
Posted
Jul 7, 2026
Apply by
August 6, 2026
Applicants
0
Early applicantFull-timeWork from Office
Job Description
ARE YOU READY to step into the **New Era (NewRA) of AI-driven banking**?
At **Accenture Newra AI Hub**, we are not just building technology, we are redefining how banking operates. As part of our strategic collaboration with Piraeus, Newra is designed to responsibly embed AI at the core of its business, moving beyond experimentation to real-world impact at scale. Built to make a real difference, Newra reflects our belief that AI creates value only when it genuinely improves people’s lives.
You will work on **advanced AI solutions** that span the full spectrum of the bank -from core banking systems to customer experience- simplifying complexity, automating critical processes and delivering measurable results where they matter most.
Joining **Newra** means becoming part of a high-performing team of innovators at the beginning of a major reinvention. This is a space for people who approach AI with depth, discipline and purpose. You will collaborate across disciplines, develop future-proof skills, and help turn technology into real-world transformation.
As an AI Security Engineer, you’ll help secure enterprise AI and GenAI systems from design through production, making sure models, prompts, agents, data flows, and integrations are protected against misuse, leakage, manipulation, and abuse. You’ll work with product, engineering, security, risk, compliance, and Responsible AI teams to threat-model AI use cases, define technical guardrails, coordinate security testing and red teaming, and embed secure-by-design controls into the AI delivery lifecycle.
**What You'll Build**
- AI security patterns and control requirements that help teams design, build, deploy, and monitor AI systems securely and consistently
- Threat models for GenAI, agentic AI, machine learning, RAG, model endpoints, data pipelines, and third-party AI platforms
- Guardrail and runtime-defense specifications embedded into AI products — input/output filtering, prompt-injection detection, data-leakage prevention, jailbreak resistance, and least-privilege boundaries for agent tool use
- AI security testing approach covering adversarial prompts, abuse cases, data exposure, insecure integrations, model/tool misuse, and pre-deployment security gates
- Secure architecture checkpoints embedded into product, data, engineering, cloud, security, compliance, and release processes
- Monitoring and response mechanisms for AI security events, including suspicious prompts, policy violations, sensitive-data exposure, tool misuse, and anomalous model behavior
- Documentation and evidence for AI security posture, risk acceptance, control effectiveness, and regulatory/model compliance
- Enablement content that helps teams understand AI threats, apply guardrails, and build secure AI products from day one
**What We Need**- Degree in Cybersecurity, Computer Science, Software Engineering, Data, AI/ML, Risk
- 4-5 years of experience in application security, cloud security, AI/ML engineering, DevSecOps, technology risk, or security engineering
- Working knowledge of AI/ML and GenAI architecture, including RAG, prompt flows, embeddings, vector databases, APIs, model endpoints, and agent/tool use
- Understanding of AI security risks: prompt injection, data leakage, model misuse, insecure plugins/tools, excessive agency, supply-chain risk, and model/prompt exfiltration
- Ability to perform AI threat modeling, define security requirements, and translate findings into practical engineering mitigations
- Experience with secure SDLC, vulnerability management, security testing, logging/monitoring, IAM, secrets management, and cloud security controls
- Ability to partner with product, engineering, data science, cloud, security operations, legal, risk, compliance, and Responsible AI teams
- Clear communicator, able to explain AI security risks, attack paths, controls, and residual risk
Nice to have:
- Exposure to LLM red teaming, adversarial testing, guardrail evaluation, or runtime AI safety/security controls
- Background in banking, regulated technology environments, DORA, EU AI Act, ISO, NIST, model-risk governance
**What's In It For You**- Competitive salary and benefits, including but not limited to: life/health insurance, performance based bonuses, monthly vouchers, company car (depending on management level), flexible work arrangements, employee share purchase plan, parental leave and various corporate discounts
- Continuous training & development through global platforms & local academy. At Accenture, we believe in bringing the best to our clients through continuous learning & improvement – from basic skills to industry-specific content – available to all our people
- Career coaching and mentorship to help you manage your career and develop professionally
- Ongoing strength and skill-based evaluation process
- Various opportunities to develop your career across a spectrum of clients, industries and projects
- Diverse and inclusive culture
- Opportunities to get involved in corporate citizenship initiatives, from volunteering to doing charity work
- Under our Brain Regain initiative, extra relocation benefits may apply
To learn more about Accenture, and how you will be challenged and inspired from Day 1, please visit our website accenture.com/gr-en/.
Key Responsibilities
- Design and implement AI security patterns and control requirements for secure AI system deployment.
- Develop threat models for GenAI, agentic AI, machine learning, RAG, and third-party AI platforms.
- Define guardrail and runtime-defense specifications including input/output filtering and prompt-injection detection.
- Execute AI security testing covering adversarial prompts, abuse cases, and pre-deployment security gates.
- Embed secure architecture checkpoints into product, data, engineering, and cloud processes.
- Establish monitoring and response mechanisms for AI security events and policy violations.
- Create documentation and evidence for AI security posture, risk acceptance, and regulatory compliance.
- Develop enablement content to help teams understand AI threats and build secure AI products.
Requirements
- Degree in Cybersecurity
- Computer Science
- Software Engineering
- Data
- AI/ML
- or Risk
Skills Required
Application securityCloud securityAI/ML engineeringDevSecOpsTechnology riskSecurity engineeringAI/ML architectureGenAI architectureRAGPrompt flowsEmbeddingsVector databasesAPIsModel endpointsAgent/tool useAI threat modelingSecure SDLCVulnerability managementSecurity testingLogging/monitoringIAMSecrets managementCloud security controlsCommunicationCollaborationProblem solvingLLM red teamingAdversarial testingGuardrail evaluationRuntime AI safety/security controlsDORAEU AI ActISONISTModel-risk governance
Benefits
- Competitive salary
- Life/health insurance
- Performance based bonuses
- Monthly vouchers
- Company car
- Flexible work arrangements
- Employee share purchase plan
- Parental leave
- Corporate discounts
- Continuous training & development
- Career coaching and mentorship
- Strength and skill-based evaluation
- Diverse and inclusive culture
- Corporate citizenship initiatives
- Relocation benefits
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