Senior AI Security Technical Architect
Location: St Louis, MO or hybrid from a Capco hub (NY, CLT,
Orlando, Chicago)
Skills Needed: AI + Cyber
Capco is seeking a Senior AI Security Technical Architect to continue to
build upon a defined enterprise AI security strategy, ensuring artificial
intelligence and generative AI capabilities are designed, deployed, and
operated in a secure, compliant, and responsible manner. This role is
responsible for aligning business objectives, technology strategy, and security
architecture to enable AI innovation with clear guardrails. The Senior AI
Security Technical Architect will establish standards, patterns, and governance
across multiple AI usage models, including third-party SaaS AI solutions,
internally developed AI/ML platforms, and emerging agentic and autonomous AI
systems. By grounding AI security practices in industry frameworks such as NIST
AI Risk Management Framework (AI RMF) and MITRE ATLAS, this role ensures AI
risks are proactively identified, communicated, and mitigated while supporting
the firm’s broader digital transformation, cloud adoption, and regulatory
obligations.
What You’ll Do
- Own and evolve
the enterprise AI security architecture and strategy, aligning business
goals, technology platforms, and risk management practices.
- Assist in
defining secure-by-design patterns and standards for AI/ML systems
- Establish and
maintain AI-specific security artifacts
- Ensure
consistent adoption of NIST AI RMF, MITRE ATLAS, CIS, ISO 27001 across AI
initiatives.
- Establish
architectural governance and enforce adherence to AI security standards
across product teams and platforms.
- Influence AI
design decisions early in the lifecycle to reduce downstream risk and
rework.
- Partner with
enterprise stakeholders to balance speed of innovation with risk tolerance
and regulatory expectations.
- Evaluate AI
frameworks, agents, vector databases, and third-party AI platforms for
security posture and enterprise readiness.
- Recommend and
rationalize AI security tooling as part of the broader enterprise security
strategy.
- Monitor
emerging AI threats, regulatory guidance, and industry best practices to
inform security strategy and standards.
What Experience You’ll Need
- Bachelor’s
degree in Computer Science, Engineering, or related field, or equivalent
practical experience.
- 8–12+ years of
experience in cybersecurity engineering or architecture within a complex
enterprise environment.
- 2–4+ years of
hands-on experience securing or reviewing AI/ML systems and platforms.
Strong understanding of:
- LLM
architectures, embeddings, and Retrieval-Augmented Generation (RAG)
patterns
- End-to-end ML
pipelines (training → validation → deployment → inference)
- AI model
supply chain risks (model registries, containers, dependencies,
open-source components)
- Zero Trust and
identity-centric security models
- Cloud security
across Azure, AWS, and GCP
- Proven ability
to influence architecture decisions and lead cross-functional initiatives
at the enterprise level.
- Excellent
communication skills, with the ability to engage senior technical and
business leaders.
What Could Set You Apart
- Security
certifications such as CISSP, CISM, CCSP, or SANS certifications.
- Experience
contributing to responsible AI practices, explainability, or bias
mitigation initiatives
- Experience
securing AI platforms in regulated industries, particularly financial
services.
- Background
supporting advanced encryption, cryptographic agility, or post-quantum
readiness.
- Demonstrated
experience in incident response and enterprise risk management.
- Understanding
of various regulatory requirements and laws, including but not limited to
NYDFS Cybersecurity Regulations and FINRA Regulations
Thanks & Regards,
Maddula Venkateshwara Reddy | ICS Global Soft
Senior. US IT RECRUITER
venkatre...@gmail.com