Sr. AI Cloud Platform Engineer

Stifel, Incorporated; St. Louis (MO); On-site; USD 150,000 - 210,000; Full time

Job summary

Stifel, Incorporated seeks a Sr. AI Cloud Platform Engineer to lead the architecture and hands-on development of secure, reusable platform capabilities for security teams.

You will design and implement integrations, data pipelines, and automation at scale, aligning with enterprise standards and cost controls. You will drive AI-enabled security capabilities, tooling, and dashboards, while mentoring engineers and partnering with Security Architecture and cloud platform teams to ensure consistent,

Qualifications

• Lead the architecture and technical design of shared capabilities across platforms and services.
• Build shared security tool integrations and reusable automation to reduce toil and duplication.
• Architect AI solutions that secure the organization’s use of AI and improve security operations.
• Develop shared data models, metrics, and dashboards for automated reporting.
• Embed IAM, secrets management, encryption, logging, and policy enforcement into platform designs.

Responsibilities

• Lead architecture and technical design of team platforms, services, APIs, data pipelines, and automation.
• Develop reusable security integrations and automation for multiple pods.
• Contribute to AI security strategy and enable secure AI adoption.
• Create and maintain common data models, dashboards, and reporting capabilities.
• Collaborate with architects to align designs with standards and cost goals.
• Mentor engineers in platform engineering and secure development practices.

Skills

Platform architecture

Automation engineering

AI/LLM security

Python

Cloud design

Tools

Terraform

CloudFormation

CDK

AWS Lambda

Step Functions

Job description

Why Stifel

Stifel strives for a culture that puts its clients and associates first: a culture where everyone belongs, everyone is welcome, and everyone contributes to the success of our clients, their careers, and the firm as a whole.

Let's talk about how you can find your place here at Stifel, where success meets success .

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 - platforms, services, integrations, APIs, data pipelines, and automation - 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 archi