Cybersecurity FDE Manager

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NieokreśloneOn-site·WarszawaFull-time

#478735·Dodano 4 dni temu·1

Źródło: Accenture

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Tech Stack / Keywords

LLMsRAGMLOpsAWS Azure GCPClaude CodeCursorGitHub CopilotOWASP LLM Top 10

Podsumowanie oferty

A production engineer embedded with a client’s security and engineering teams, securing and governing production AI systems. The role leads security architecture and engineering for LLMs, multi-agent workflows, RAG solutions, and MLOps infrastructure.

Wymagania

Extensive engineering experience in production environments and cybersecurity expertise in at least one area: AppSec, SecOps / detection engineering, cloud security, IAM, offensive security / penetration testing, or GRC.
Hands-on experience designing and deploying agentic AI solutions in production environments; practical implementation experience is essential.
Strong experience owning end-to-end security delivery in client-embedded or production environments; experience limited to internal advisory or compliance activities is not sufficient.
Solid experience with cloud platform security across at least one provider (AWS, Azure, or GCP), including IAM, network security, secrets management, and AI service security configurations.
Bachelor’s degree or equivalent professional experience; an Associate’s degree is also considered alongside relevant work experience.
Proven ability to communicate security risk in business terms and translate threat exposure into risk-adjusted investment rationale for a CISO or CFO.
Experience managing, developing, and performance-managing a team of engineers; setting individual development plans and conducting career conversations.

Obowiązki

AI Security Architecture & Engineering:

Lead the design and implementation of security architectures for production AI systems, including LLMs, multi-agent workflows, RAG solutions, and MLOps infrastructure.
Develop AI-powered security solutions, including threat detection systems, automated response tools, security assessment frameworks, and governance automation, using tools such as Claude Code, Cursor, or GitHub Copilot.

AI Threat Management & Cloud Security:

Lead threat modeling and implement security controls for AI-specific risks, including prompt injection, model extraction, adversarial attacks, and AI supply chain vulnerabilities, aligned with OWASP LLM Top 10.
Design and oversee enterprise AI security controls covering identity and access management, data pipelines, model deployment, and system integrations across AWS, Azure, or GCP.

AI Governance & Compliance:

Lead implementation of AI governance and risk management frameworks, including the EU AI Act, NIST AI RMF, and model risk management practices for production AI environments.

Client Advisory & Strategy:

Advise senior client stakeholders, including CISOs and CTOs, on AI security strategies, architecture roadmaps, governance operating models, and risk-based investment decisions.
Lead architecture design sessions, threat modeling workshops, and hands-on coding sessions with client engineering and security leadership teams.

Practice Development:

Develop reusable security frameworks, playbooks, and accelerators to support consistent delivery across multiple client engagements and contribute to the growth of the Secure AI practice.

Inne informacje

Candidates must be based in Poland or the Czech Republic.
Travel may be required, ranging from 0% to 100% depending on business need and client requirements.

Accenture

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