Sr Engineer AI Platform

Academy•Katy, TX

1d•Onsite

About The Position

Design, implement, operate, and continuously improve enterprise platforms and integration capabilities that support AI agents and generative AI solutions. Help teams move approved AI solutions from prototype to reliable production use across Microsoft Azure, Microsoft 365, Power Platform, Google, and other approved enterprise AI technologies. Provide technical leadership for secure, scalable, observable, cost-managed, governed, and supportable platform services across development, test, and production environments. Establish standards for source control, release management, deployment pipelines, environment separation, production readiness, and operational support. Implement governance controls for inventories, ownership, risk tiering, identity, access, data protection, runtime protection, audit logging, and periodic recertification. Manage model access, quotas, capacity, private networking, endpoints, and onboarding controls. Build telemetry and consumption controls, enable secure integrations with enterprise systems, embed automated evaluation and compliance checks, and document reusable patterns. Lead technical initiatives, mentor engineers, and evaluate emerging capabilities that can improve security, reliability, scalability, efficiency, and adoption. Partner across AI engineering, Cybersecurity, Identity, Enterprise Architecture, Data, Legal, Finance, and business teams to ensure AI platforms and integrations are secure, governed, supportable, and cost effective. Work directly with engineers, platform users, solution owners, business power users, and approved citizen developers, providing standards, documentation, enablement materials, technical guidance, and mentorship to support safe and consistent adoption.

Requirements

Bachelor's degree in Computer Science, Information Technology, Engineering, Data, or a related field, or equivalent practical experience.
7+ years of experience in platform engineering, infrastructure engineering, DevOps, MLOps, cloud engineering, integration engineering, or related disciplines.
2+ years of experience building or operating platforms for large language model, generative AI, AI agent, or intelligent automation workloads.
Experience designing, implementing, and supporting enterprise-scale cloud platforms, shared services, or internal developer platforms used by multiple teams.
Hands-on experience with Microsoft Azure, Microsoft 365, Entra ID, Copilot Studio, Power Platform administration, Azure AI services, or comparable enterprise platforms.
Experience implementing infrastructure as code, source control, release gates, CI/CD pipelines, environment management, and production support practices.
Experience integrating enterprise applications through REST APIs, OAuth, service-to-service authentication, connectors, workflow tools, and systems of record.
Experience implementing platform monitoring, incident response, usage telemetry, cost controls, audit logging, and operational reporting.
Experience leading complex technical initiatives, establishing standards, and mentoring or guiding engineers and platform users.
Strong knowledge of cloud platform architecture, AI platform engineering, environment strategy, networking, identity, access controls, and enterprise security practices.
Deep understanding of authentication, authorization, least-privilege access, data protection, auditability, privacy, and responsible AI controls.
Ability to design and operate development, test, and production environments based on solution risk and support requirements.
Practical knowledge of Azure AI services, Copilot Studio, Power Platform, Microsoft 365, Microsoft Graph, Entra ID, Purview, Defender, or comparable technologies.
Experience with infrastructure as code and CI/CD technologies such as Bicep, Terraform, Azure DevOps, GitHub Actions, or comparable solutions.
Experience with observability, incident management, performance monitoring, usage analytics, cost telemetry, and consumption controls.
Ability to design reusable identity, logging, evaluation, connector, integration, and deployment patterns for AI-enabled solutions.
Proficiency in Python, PowerShell, or another scripting language used for platform automation.
Strong analytical, troubleshooting, documentation, and problem-solving skills in distributed enterprise environments.
Ability to influence cross-functional teams, explain technical controls to technical and non-technical stakeholders, and provide technical leadership and mentorship.
A team-first attitude and willingness to step in wherever needed.

Nice To Haves

Retail, regulated, or multi-site enterprise experience.
Microsoft Azure, Microsoft Power Platform, identity and access management, cloud security, DevOps, MLOps, or related platform certification.

Responsibilities

Design, implement, operate, and continuously improve enterprise AI platforms and integration capabilities.
Move approved AI solutions from prototype to reliable production use across approved enterprise technologies.
Provide technical leadership for secure, scalable, observable, cost-managed, governed, and supportable platform services across development, test, and production environments.
Establish standards for source control, release management, deployment pipelines, environment separation, production readiness, and operational support.
Implement governance controls for inventories, ownership, risk tiering, identity, access, data protection, runtime protection, audit logging, and periodic recertification.
Manage model access, quotas, capacity, private networking, endpoints, and onboarding controls.
Build telemetry and consumption controls, enable secure integrations with enterprise systems, and embed automated evaluation and compliance checks.
Document reusable patterns and evaluate emerging capabilities to improve security, reliability, scalability, efficiency, and adoption.
Lead technical initiatives and mentor engineers and platform users.
Partner with AI engineering, Cybersecurity, Identity, Enterprise Architecture, Data, Legal, Finance, and business teams.
Provide standards, documentation, enablement materials, and technical guidance to engineers, platform users, solution owners, business power users, and approved citizen developers.