Design end‑to‑end security architecture for AI/ML systems, multi‑cloud infrastructure, and modern application ecosystems.
Build secure design patterns for APIs, microservices, distributed systems, and serverless workloads.
Define cloud and application security standards for engineering and platform teams.
Lead architecture reviews and guide critical initiatives across cloud and AI environments.
Implement advanced controls for ML pipelines and generative AI platforms.
Identify and mitigate risks such as prompt injection, model poisoning, AI supply chain vulnerabilities, and data leakage.
Partner with data science teams to ensure secure training, deployment, and governance of AI models.
Champion secure and responsible AI adoption throughout the enterprise.
Architect secure solutions across AWS, Azure, and GCP.
Define identity, segmentation, encryption, workload protection, and observability patterns.
Secure Kubernetes, containers, and serverless workloads at scale.
Build guardrails that empower engineering teams to innovate safely.
Integrate security into CI/CD pipelines and the full SDLC.
Deploy and optimize automated tools for SAST, DAST, SCA, IaC scanning, and container security.
Drive shift‑left practices and foster engineering‑led security adoption.
Align architecture with frameworks like NIST RMF, SOC, SOX, and zero‑trust principles.
Guide risk assessments, compliance efforts, and enterprise control design.
Ensure secure‑by‑design principles are consistently embedded into systems and processes.
Partner with engineering, cloud, product, IT, and business leaders to deliver secure solutions.
Influence decisions across executive and technical stakeholders.
Mentor and develop security engineers and architects.
Foster a security‑first, innovation‑driven culture.
Requirements
10+ years of professional experience in information security spanning multiple domains, including cloud, application, and platform security.
Proven experience designing and implementing large‑scale enterprise security architectures across modern engineering and cloud environments.
Deep technical expertise in cloud security (AWS, Azure, GCP), DevSecOps, secure SDLC, and modern application architectures (APIs, microservices, containers, Kubernetes, serverless).
Hands‑on experience or strong foundational understanding of AI/ML security , including risks such as data leakage, model manipulation, and supply chain vulnerabilities.
Strong ability to influence and collaborate with senior leaders, engineering teams, cloud operations, and cross‑functional stakeholders.
Demonstrated capability to translate complex technical risks into clear business impact for executive audiences.
Exceptional architectural thinking, communication, and strategic problem‑solving skills.
Experience mentoring and developing security engineers , helping foster a high‑performance, security‑first engineering culture.
Tech Stack
AWS
Azure
Cloud
Distributed Systems
Google Cloud Platform
Kubernetes
Microservices
SDLC
Benefits
medical, dental, vision, life and disability plans
well-being incentives
parental leave
paid time off
certain paid holidays
tax saving accounts (FSA, HSA)
401(k) retirement benefit
Employee Stock Purchase Plan
tuition assistance
entertainment and retail discounts
Non-exempt employees are eligible for overtime pay, if applicable.