Director, AI - Cyber Security I

Fiserv•Columbus, OH

7d•$127,500 - $204,000•Onsite

About The Position

This is your chance to build something from scratch: a brand-new AI-driven cybersecurity engineering capability at one of the largest fintechs on the planet. As Senior Advisor, Software Engineering on our AI Security Engineering team, you won't be babysitting legacy tools – you'll be architecting and scaling the agentic AI frameworks, platforms, and cloud-native systems that define how Fiserv detects, investigates, and shuts down threats for years to come. You'll team up across cybersecurity, cloud engineering, data engineering, application development, and enterprise architecture to ship secure, production-grade AI solutions on Google Cloud – with the runway to set the direction, not just follow someone else's roadmap. This is a hands-on, individual-contributor role with no direct reports – your impact comes from what you build and architect, not from managing a team. If you want your fingerprints on the next generation of AI-powered cyber defense at enterprise scale, this is your seat at the table.

Requirements

10+ years of experience in software engineering, building enterprise-scale applications and platforms using Python and modern software development practices.
10+ years of experience designing and operating cloud-native solutions on Google Cloud Platform or a comparable major cloud provider.
Hands-on experience building or integrating generative AI and agentic AI systems, including LLMs, RAG pipelines, embeddings, vector databases, and orchestration frameworks.
Strong understanding of cybersecurity domains such as threat detection, identity and access management, SIEM/SOAR, and security operations, with the ability to translate them into AI-driven engineering solutions.
Experience with containerization and orchestration technologies (Kubernetes, Docker) and modern CI/CD and MLOps practices.
Excellent communication skills, with the ability to influence technical direction and enterprise adoption across cross-functional technical and business stakeholders.
Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or a related field, or equivalent professional/military experience.

Nice To Haves

Experience in financial services or another highly regulated industry.
Familiarity with additional enterprise security platforms such as CrowdStrike, Splunk, or comparable SIEM/SOAR and GRC tooling.
Background applying Zero Trust and Secure-by-Design principles to AI/ML platform architecture.
Relevant certifications (e.g., Google Cloud Professional certifications, CISSP, or AI/ML-specific credentials).
Experience mentoring engineers or leading cross-functional technical initiatives at scale.

Responsibilities

Design, build, and ship AI-powered cybersecurity capabilities across threat detection, anomaly identification, identity and access risk analysis, security operations automation, incident response orchestration, and cyber threat intelligence.
Architect and stand up multi-agent and agentic AI frameworks that power enterprise cybersecurity use cases, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, vector search, and knowledge retrieval systems.
Lead the engineering and delivery of scalable, cloud-native AI security platforms on Google Cloud using tools like Vertex AI, Gemini, BigQuery, Pub/Sub, Dataflow, Cloud Run, Cloud Functions, and Google Kubernetes Engine (GKE).
Integrate AI capabilities directly into enterprise cybersecurity platforms and services, including Identity and Access Management (IAM), Privileged Access Management (PAM), secrets management, SIEM, SOAR, GRC, and security telemetry platforms.
Set the engineering standards and lifecycle practices for AI platforms – model training pipelines, automated deployment, monitoring, evaluation, drift detection, Infrastructure as Code, and CI/CD for machine learning workloads.
Bake security, privacy, compliance, and responsible AI practices into every platform you build, applying Zero Trust principles, Secure-by-Design methods, and defenses against prompt injection, adversarial machine learning threats, data poisoning, model manipulation, and unauthorized access.
Partner with cross-functional technical and business teams to turn cybersecurity and business requirements into scalable AI solutions, while shaping architecture, technical direction, and enterprise-wide adoption of modern AI engineering practices.