Senior AI Security Engineer Job at Citi (Budapest)

Senior AI Security Engineer

Citi

Location:
Hungary , Budapest

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

22713830.00 - 38083370.00 HUF / Month

Save Job

Apply Position

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

Additional Information:

Job Posted:
March 20, 2026

Employment Type:

Fulltime

Work Type:

Hybrid work

Citi - All Job Offers

Job Link Share: