AI Architect I

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

📋 Description

• Create comprehensive architectures for agentic AI solutions, covering orchestration, runtime execution, workflow management, tool invocation, system integrations, evaluation, observability, and supportability.

• Convert product requirements, business workflows, and customer use cases into technical designs and actionable implementation plans.

• Establish reusable patterns for multi-step agent behavior, task routing, handoffs, cross-system interactions, state management, and coordination among multiple agents.

• Collaborate with AI Platform teams to leverage shared capabilities in orchestration, runtime, evaluation, reporting, monitoring, and developer tooling.

• Work alongside engineering teams through architecture reviews, design guidance, technical documentation, and assessments for production readiness.

• Assess tradeoffs related to scalability, reliability, performance, security, maintainability, cost, developer experience, and delivery speed.

• Define integration patterns for APIs, enterprise systems, data sources, tools, model services, and Model Context Protocol capabilities.

• Set observability requirements, which include logging, metrics, traces, dashboards, alerts, debugging workflows, and operational reporting.

• Collaborate with QA/Eval teams on evaluation criteria, regression coverage, testing strategies, and quality assurance controls.

• Assist in release planning, launch-readiness reviews, production monitoring, incident response, and post-release enhancements.

• Identify recurring solution patterns and propose shared product or platform capabilities.

• Contribute to architecture standards, reference designs, technical decision records, implementation guidance, and reusable documentation.

• Aid teams in applying responsible AI, privacy, security, governance, and human oversight protocols.

• Communicate technical decisions, dependencies, risks, and recommendations to engineering, product, operations, and business stakeholders.

⛳️ Requirements

• Proven experience in designing or building backend systems, distributed applications, workflow platforms, integration services, developer platforms, cloud applications, or AI-enabled solutions.

• Working knowledge of APIs, asynchronous processing, service coordination, event-driven architectures, stateful systems, and enterprise integrations.

• Understanding of architectural principles regarding scalability, reliability, performance, availability, maintainability, security, and production support.

• Familiarity with LLM-based applications, AI agents, retrieval techniques, prompt and context management, tool invocation, workflow automation, or model-driven products.

• Capability to translate business and workflow requirements into feasible technical architectures.

• Experience with cloud services, deployment pipelines, monitoring, logging, dashboards, and troubleshooting in production environments.

• Knowledge of testing, evaluation, regression coverage, release readiness, and operational support for production systems.

• Ability to assess technical alternatives and articulate architectural tradeoffs to both technical and non-technical stakeholders.

• Excellent written and verbal communication skills, including the ability to create clear diagrams, design documents, decision records, and implementation guidance.

• Strong collaborative abilities across engineering, product, QA/Eval, security, infrastructure, operations, and support teams.

• Capacity to thrive in a dynamic technical environment.

• Preferred: experience in designing or implementing production LLM applications, AI agents, workflow automation, or intelligent assistant solutions.

• Preferred: familiarity with agent orchestration frameworks, model gateways, evaluation frameworks, vector search, retrieval-augmented generation, and AI observability.

• Preferred: experience in integrating AI solutions with enterprise platforms, internal services, APIs, data sources, and third-party tools.

• Preferred: familiarity with Model Context Protocol, tool integration primitives, structured outputs, agent memory, workflow state, and multi-agent patterns.

• Preferred: experience with responsible AI practices, including safety controls, access management, data protection, human oversight, and auditability.

• Preferred: experience in creating reusable reference architectures, platform patterns, technical standards, or architecture governance.

• Preferred: familiarity with production incident management, reliability engineering, deployment strategies, and post-release support.

• Relevant cloud, software architecture, data, security, or AI certifications are advantageous but not mandatory.

🏝️ Benefits

• Health, dental, and vision insurance.

• Retirement savings plan with company match.

• Paid time off and holidays.

• Opportunities for professional development.

• Performance-based bonuses depending on position.

• Certain roles may qualify for additional rewards, including annual bonuses and sales incentives based on the applicable plan, role, and individual performance.