Senior AI Platform Engineer

About the role

Alpaca is establishing an AI Enablement function to transition from ad hoc AI experiments to widespread, sustainable productivity gains. As a Senior AI Platform Engineer, you will be responsible for the technical foundation that makes this transformation possible. You will construct and manage the infrastructure, integrations, execution methods, and self-service tools that empower engineering and business teams to utilize AI securely and at scale. Your work will involve transforming individual setups and temporary tools into reusable infrastructure, secure deployment standards, and standardized onboarding processes.

Key facts

What you'll do

• Develop and maintain the integration layer that supports AI workflows across the company.
• Design and deploy execution environments for AI agents and autonomous workflows, including defining isolation boundaries and access controls.
• Create reusable platform services, standard workflows, and self-service templates to simplify AI adoption for various teams.
• Streamline the onboarding process for AI tools to ensure reliability for both technical and non-technical users, reducing reliance on manual support.
• Establish and enforce technical guidelines for agent execution, evaluation processes, and deployment.
• Collaborate with Security and IT teams to implement secure deployment patterns for advanced AI capabilities.
• Manage the AI governance layer, including access permissions, audit trails, approval mechanisms, and deployment restrictions for agentic workflows.
• Set the operational standards for reliability and observability for AI-specific infrastructure.
• Serve as the primary technical point of contact for resolving platform or onboarding issues that impede AI project rollouts.
• Convert complex exception handling into repeatable processes to minimize dependence on individual expertise.

Requirements

• A minimum of 8 years of experience in software, platform, infrastructure, or related engineering fields.
• Demonstrated hands-on experience building agentic AI systems, such as LLM-powered workflows, tool-calling agents, evaluation loops, or autonomous execution, utilizing frameworks like Claude SDK, Google Agent Development Kit (ADK), or LangGraph. This experience should focus on agentic AI, not traditional ML or data pipelines.
• Proficiency with Google Cloud Platform (GCP).
• Substantial experience with APIs, authentication mechanisms (including OAuth), secrets management, CLI tooling, and deployment strategies.
• Experience with cloud-native systems, including containerization, orchestration (Kubernetes), and infrastructure-as-code practices.
• Proven ability to implement AI governance controls, such as access boundaries, audit logging, approval workflows, and safe deployment standards for autonomous systems.
• Adaptability to work effectively in both fast-paced, low-process environments and more structured, compliance-focused settings.
• A strong preference for simplification, standardization, and operational stability over unique, complex solutions.
• Excellent communication skills, with the ability to collaborate effectively with engineering, security, and non-technical stakeholders.

Nice to have

• Experience deploying agentic systems in production that interact with external tools like file systems or APIs.
• Familiarity with Google Agent Engine (Vertex AI Agent Builder) or comparable managed agent execution platforms.
• Direct experience with AI-native coding environments and strong opinions on their integration into engineering workflows.
• Experience designing or operating agent sandboxing, isolation, or evaluation frameworks.
• A track record of building self-service developer platforms or standard workflows adopted by multiple teams.
• Prior startup experience, with a demonstrated ability to build durable solutions under resource constraints.
• Knowledge of the fintech industry, regulated environments, or compliance-aware deployment practices.

Skills & tools

• Agentic AI Systems (LLM-powered workflows, tool-calling, evaluation loops, autonomous execution)
• Claude SDK, Google Agent Development Kit (ADK), LangGraph
• Google Cloud Platform (GCP)
• APIs, OAuth, Secrets Management, CLI Tooling
• Containerization, Kubernetes, Infrastructure-as-Code
• AI Governance Controls (Access Boundaries, Audit Logging, Approval Workflows)
• GCP (Google Cloud Platform)

Practical notes

• Competitive salary and stock options.
• Health benefits.
• A one-time USD $500 home-office setup stipend for new hires.
• A monthly stipend of USD $150 provided via a Brex Card.
• Alpaca is an equal opportunity employer committed to diversity.