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Citi Logo Citi · IT - Software Development

Senior AI Security Engineer

Hungary, Budapest · Job Posted March 20, 2026
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Job Description

The Senior AI Security Engineer is a technical leader and engineering manager within CISO's AI security incubation function, enabling teams to move from ideation to working proof-of-concept and through to production-ready use cases. This role combines hands-on technical contribution with people management — owning the Incubator Environment that accelerates how cybersecurity teams discover, prototype, and validate AI-powered solutions, while leading and developing the engineering team that makes it happen.

Job Responsibility

  • Agentic AI Engineering & Use Case Incubation (40%): Own and evolve the Incubator Environment — the platform and tooling that enables CISO teams to move from idea to working PoC to validated use case
  • Partner with cybersecurity domain teams to understand their challenges, identify high-value AI use cases, and rapidly prototype agentic solutions
  • Design, build, and deploy agentic AI systems that autonomously perform cybersecurity tasks — including threat analysis, security control validation, intelligent triage, and response orchestration
  • Architect multi-agent orchestration systems, defining how AI agents collaborate, delegate, and escalate across security workflows
  • Implement robust agent infrastructure: tool use frameworks, memory and context management, planning/execution loops, guardrails, and human-in-the-loop controls
  • Build and maintain RAG pipelines, knowledge retrieval systems, and dynamic context assembly that underpin agent decision-making
  • Shepherd validated use cases through to production readiness and handoff to the dedicated product support team
  • Drive adoption and effective use of AI development tooling (Devin, GitHub Copilot, Claude Code) to maximize team velocity
  • Make key technical decisions on architecture, technology selection, and build-vs-integrate trade-offs
  • Incubator Platform & Technical Architecture (25%): Design and maintain the Incubator Environment architecture — a scalable, secure platform that enables rapid prototyping and validation of agentic AI use cases
  • Build reusable components, templates, and patterns that lower the barrier for new use case development across CISO domains
  • Define integration patterns between AI agents and existing CISO systems (SOC platforms, vulnerability management, threat intelligence tools, SOAR)
  • Establish observability, monitoring, and evaluation frameworks for agentic systems — including agent trace logging, decision auditing, and performance benchmarking
  • Design safety and containment architectures for autonomous agents: sandboxing, permission boundaries, output validation, and escalation triggers
  • Set engineering standards, define development practices, and establish quality gates that ensure PoCs are built to a standard that supports production handoff
  • People Leadership & Team Development (20%): Lead, develop, and manage a team of engineers, including performance management, objective setting, and career development
  • Lead hiring and technical evaluation for new team members
  • Build a high-performing engineering culture that balances speed with quality
  • Mentor and coach engineers on agentic AI technologies, secure development practices, and engineering excellence
  • Provide technical guidance through code reviews, architecture decisions, and pair programming on complex features
  • Shape the "human + AI" operating model — designing how engineers work alongside AI development tools for maximum output
  • Stakeholder Engagement & Communication (15%): Act as a senior engineering voice to the Head of GenAI Security and wider stakeholders
  • Present use case demos, technical strategy, and incubation outcomes at executive level
  • Partner with AI Architecture & Advisory team, Cybersecurity Technology, and the dedicated product support team on cross-functional initiatives
  • Translate complex AI/security engineering concepts into business language for senior leadership
  • Collaborate with CISO domain teams to identify use case opportunities and communicate what's possible with agentic AI

Requirements

  • 8-10+ years of experience in software engineering, with demonstrable experience as a technical lead or engineering manager
  • Python mastery: Deep, hands-on experience building and maintaining production-grade Python applications and services
  • LLM engineering: Practical experience with LLM APIs (OpenAI, Anthropic, Google), prompt engineering, model evaluation, and input/output guardrails
  • Production systems: Track record of deploying and operating AI/ML systems in production at enterprise scale
  • Software engineering fundamentals: Clean code, design patterns, testable architecture, CI/CD, infrastructure-as-code
  • 3+ years leading or managing engineering teams, including performance management, hiring, and career development
  • Track record of delivering complex software products in environments where priorities shift rapidly
  • Experience setting engineering standards and driving quality across a team's output
  • Demonstrated ability to mentor and develop engineers through code review, architectural guidance, and knowledge sharing
  • Proven capability to attract, develop, and retain engineering talent
  • Cybersecurity understanding: Familiarity with SOC operations, threat detection, vulnerability management, or incident response — sufficient to build effective security tools
  • Regulated environment experience: Understanding of working within governance, compliance, and risk management frameworks (financial services preferred but not essential)
  • Enterprise software delivery: Experience building products that serve hundreds or thousands of users within large organizations

Nice to have

  • AI red teaming: Experience with adversarial attacks on LLMs and agentic systems, prompt injection defense, agent manipulation, output filtering
  • MCP (Model Context Protocol): Experience building or integrating MCP servers, tool registries, and resource providers for agentic systems
  • Agent frameworks: Hands-on experience with frameworks such as LangGraph, CrewAI, AutoGen, Claude Agent SDK, or custom agent architectures
  • Cloud-native architecture: Kubernetes/OpenShift, containerized deployments, cloud platforms (AWS, Azure, GCP)
  • Observability for agentic systems: Agent trace logging, decision audit trails, performance benchmarking, LLM evaluation frameworks
  • Financial services experience: Previous role at a major bank, fintech, or financial technology vendor
  • AI development tools: Experience using AI-assisted development tools (Devin, Copilot, Claude Code, Cursor) to accelerate engineering output
  • Open-source contributions: Active participation in relevant AI/ML or security communities
  • Certifications: CISSP, AWS/Azure Solutions Architect, or relevant AI/ML certifications from major cloud providers

What we offer

  • Cafeteria Program
  • Home Office Allowance (for colleagues working in hybrid work models)
  • Paid Parental Leave Program (maternity and paternity leave)
  • Private Medical Care Program and onsite medical rooms at our offices
  • Pension Plan Contribution to voluntary pension fund
  • Group Life Insurance
  • Employee Assistance Program
  • Access to a wide variety of learning and development programs, online course libraries and upskilling platforms, such as Udemy and Degreed
  • Flexible work arrangements to support you in managing work - life balance
  • Career progression opportunities across geographies and business lines
  • Socially active employee communities with diverse networking opportunities
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