Senior AI Platform Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of the connector and service integration layer that facilitates AI workflows throughout the organization.

• Design and deliver execution environments for agents and advanced AI workflows, incorporating isolation boundaries and access controls.

• Develop reusable platform services, optimized paths, and self-service templates that minimize setup challenges for teams utilizing AI.

• Streamline the onboarding process to ensure it functions consistently for both developers and non-developers, eliminating the need for manual intervention or informal knowledge sharing.

• Establish and uphold technical standards for agent execution, evaluation processes, and deployment strategies.

• Collaborate with Security and IT to implement deployable patterns for high-risk AI functionalities.

• Manage the AI governance framework, which includes access controls, audit trails, approval criteria, and deployment limits for agentic workflows.

• Set the standards for reliability, observability, and operational excellence for AI-centric infrastructure.

• Serve as the technical point of contact for onboarding or platform challenges that hinder deployment.

• Mitigate the company's reliance on individual efforts by transforming exception handling into systematic processes.

⛳️ Requirements

• Over 8 years of experience in software, platform, infrastructure, or related engineering positions.

• Practical experience in building agentic AI systems, including LLM-powered workflows, tool-calling agents, evaluation loops, or autonomous execution — utilizing frameworks such as the Claude SDK, Google Agent Development Kit (ADK), LangGraph, or similar. Not classical ML or data pipelines.

• Hands-on experience with GCP; familiarity with Google Cloud is essential.

• Proficient in APIs, authentication, OAuth, secrets management, CLI tools, and deployment methodologies.

• Experience with cloud-native systems, including containers, orchestration (Kubernetes), and infrastructure-as-code.

• Familiarity with implementing AI governance controls: access limits, audit logging, approval processes, and safe deployment practices for higher-autonomy systems.

• Ability to operate effectively in both agile, low-process settings and more organized, compliance-focused environments. You know when to expedite and when to take a measured approach.

• Strong inclination towards simplification, standardization, and operational reliability over complex, one-off solutions.

• Excellent communication abilities to collaborate with engineering teams, security personnel, and non-technical stakeholders.

🏝️ Benefits

• Competitive Salary & Stock Options

• Health Benefits

• New Hire Home-Office Setup: One-time USD $500

• Monthly Stipend: USD $150 per month via a Brex Card