What You'll Be Doing
The Sr. AI Cloud Platform Engineer is a member of the Security Engineering & Automation team, the security organization's shared build capability, and is responsible for the platform architecture and hands-on engineering of secure, reusable capabilities that enable security teams to operate more efficiently and consistently. This role architects and develops shared security platforms, tool integrations, AI-enabled security capabilities, metrics and dashboarding services, proofs of concept, and automation that removes recurring manual work, built once and designed for adoption by multiple security pods rather than as one-off solutions. Operating with a high degree of autonomy, this role partners with Security Architecture and cloud platform architects to align team-owned solutions with organizational standards and strategic direction. The team operates under a clear contract, Security Engineering & Automation builds, and consuming pods configure, run, and report.
What We're Looking For
- Lead the architecture and technical design of the team's shared capabilities 1 platforms, services, integrations, APIs, data pipelines, and automation 1 built to be secure, scalable, resilient, and reusable.
- Build shared security tool integrations and reusable automation that eliminate manual toil, reduce duplicated engineering effort, and improve consistency across security pods.
- Architect AI solutions that both secure the organization's use of AI and apply AI to improve security operations, analysis, and decision support.
- Build and maintain shared metrics, data, and dashboarding capabilities, including common data models and integration patterns, that enable automated, business-readable reporting across the security organization.
- Partner with Security Architecture to embed security requirements, approved patterns, controls, and risk decisions into platform designs, and collaborate with enterprise and cloud platform architects to align with broader technology strategies and standards.
- Translate business, security, operational, and regulatory requirements into platform designs and executable implementation plans.
- Develop infrastructure as code using Terraform, CloudFormation, or CDK, and build automation and integrations using Python, Bash, PowerShell, AWS Lambda, Step Functions, APIs, and event-driven and workflow orchestration services.
- Embed identity and access management, secrets management, encryption, network controls, data protection, logging, monitoring, and policy enforcement into team-owned solutions.
- Conduct proofs of concept and technical evaluations to validate solution viability and inform build-versus-buy decisions, assessing technologies for technical fit, security, interoperability, supportability, cost, and reuse potential.
- Create reusable reference architectures, implementation patterns, technical standards, and onboarding guidance, and contribute to the team's service catalog, including available capabilities, engagement criteria, and ownership expectations.
- Define consumption, configuration, and support boundaries for team-built services in partnership with product management and consuming pods, along with measurable outcomes such as adoption, toil reduction, onboarding time, and data freshness.
- Maintain the reliability, availability, observability, and security of shared team-owned platforms and their CI/CD and operational tooling, and support incidents and root-cause analysis while pod-specific operations, triage, and tool administration remain with the consuming pod.
- Publish architecture diagrams, decision records, runbooks, and service documentation, and communicate evaluations, proof-of-concept results, roadmaps, and delivered business value through planning forums, demonstrations, and stakeholder reviews.
- Mentor engineers and promote strong platform engineering, secure development, automation, and architecture practices within the team.
What You'll Bring
- Strong analytical and problem-solving skills with the ability to identify manual toil and design reusable capabilities that eliminate it.
- Ability to effectively communicate technical topics and architectural decisions to technical and non-technical audiences.
- Deep understanding of platform architecture principles, including scalability, reliability, observability, interoperability, and cost management.
- Understanding of AI and LLM-based systems, including generative AI, agentic workflows, and their security considerations.
- Demonstrated ability to operate independently, lead technical design efforts, prioritize workload, and collaborate across organizational boundaries.
- Experience architecting and developing reusable cloud or platform capabilities 1 integrations, automation, APIs, or data pipelines 1 used by multiple teams.
- Experience conducting proofs of concept, technical evaluations, and build-versus-buy assessments.
- Experience incorporating security requirements and controls into cloud and platform solutions in partnership with Security Architecture or comparable governance functions.
- Experience designing for measurable outcomes such as adoption, toil reduction, reliability, and onboarding efficiency.
Education & Experience
- Minimum Required: Bachelor's degree in Computer Science, Information Systems, Computer Engineering, Software Engineering, Data Science, Cybersecurity, or related field, or a related combination of education and experience.
- Minimum Required: 6+ years of platform, infrastructure, DevOps, cloud, automation, integration, security engineering, or software engineering experience; 3+ years of hands-on AWS experience in production environments.
- Minimum Required: Experience applying AI, machine learning, or generative AI to automation, engineering, or security use cases.
- Preferred: Experience with metrics platforms, APIs, or workflow orchestration.
- Preferred: Experience supporting regulated or financial-services environments.
Licenses & Credentials
- Minimum Required: AWS Certified Solutions Architect 1 Associate or Professional, or equivalent demonstrated AWS expertise.
- Preferred: AWS Certified DevOps Engineer 1 Professional.
- AWS Certified Security 1 Specialty, AWS Certified Machine Learning 1 Specialty, HashiCorp Terraform Associate, CCSP, CISSP, or comparable cloud, AI, or platform engineering credentials, is a plus.
Systems & Technology
- Deep hands-on AWS experience, including services such as EC2, VPC, IAM, Lambda, ECS/EKS, S3, RDS, CloudWatch, Organizations, and Control Tower.
- Experience with infrastructure as code (Terraform, CloudFormation, or CDK) and scripting and automation using Python, Bash, PowerShell, or similar languages.
- Experience designing and integrating APIs, event-driven services, workflow automation, and third-party security technologies for adoption by multiple teams.
- Experience with AI and machine learning services such as Amazon Bedrock, Amazon SageMaker, Azure OpenAI, or OpenAI APIs, including generative AI, retrieval-augmented generation, agentic workflows, and model gateways.
- Working knowledge of cloud and platform security, including IAM least privilege, secrets management, encryption, network security, logging, monitoring, data protection, and policy-as-code.
- Preferred: Metrics, dashboarding, and data platforms such as Grafana, Power BI, QuickSight, or OpenSearch.
- Preferred: CI/CD tooling (GitHub Actions, Azure DevOps, or Jenkins), container orchestration (Docker, Kubernetes, or ECS/EKS), and observability tooling (Datadog, Prometheus, or OpenTelemetry).
- Preferred: Experience with OPA, AWS Config, Service Control Policies, cloud security posture management, data-loss prevention, or automated guardrail technologies.
