Sr. AI Platform Architect

Parts Town•Addison, IL

1d•$182,523 - $203,437

About The Position

The Senior AI Platform Architect owns the architecture, standards, and technical direction of Parts Town’s enterprise AI ecosystem, spanning platforms, models, agents, and integrations. The role ensures AI solutions are scalable, secure, compliant, and aligned with business goals. As a hands-on senior individual contributor, the architect designs and guides delivery of AI agents, assistants, RAG solutions, and AI-powered workflows in partnership with data, infrastructure, security, application, and business teams. The position has a path to platform leadership as the AI function grows. The ideal candidate combines enterprise architecture expertise with hands-on experience building AI solutions using modern agent frameworks, APIs, function calling, Model Context Protocol (MCP), enterprise SaaS platforms, and cloud-native technologies. Parts Town describes its team as collaborative, inclusive, positive, and supportive, with an emphasis on responsibility, improving the workplace, social events, celebrating milestones, transparency, growth, and work-life balance. The role offers an annual salary range of $182,523.26 to $203,437.39, with compensation based in part on qualifications, experience, and geographic location. Parts Town is a pay-for-performance company; some roles offer profit sharing and an annual bonus depending on the role. The company also describes a comprehensive benefits package and is an equal opportunity employer.

Requirements

Bachelor’s degree in computer science, engineering, or a related technical discipline.
8+ years shaping enterprise architecture, software engineering, or platform engineering initiatives at scale.
Successfully designed, built, and deployed enterprise-grade AI solutions and intelligent agent ecosystems.
Deep expertise in agentic AI, including MCP, function calling, tool orchestration, and context management strategies.
Strong understanding of the AI landscape, including RAG, LLMs and SLMs, semantic search, AI evaluation, monitoring, and responsible AI practices.
Proficiency in programming languages such as Python, Java, and TypeScript.
Experience in modern development environments, using frameworks such as React, Rails, Spring, or comparable technologies.
Experience architecting and delivering microservices, event-driven systems, APIs, and enterprise integration solutions.
Strong cloud architecture expertise, including CI/CD pipelines, infrastructure-as-code, and observability best practices.
Hands-on experience scaling containerized workloads using Docker, Kubernetes, and autoscaling technologies.
Knowledge of enterprise security, identity management, RBAC, privacy, and regulatory requirements.
Exceptional communication skills, including influencing stakeholders, explaining complex technical concepts, and building cross-functional partnerships.

Nice To Haves

Experience with AI coding tools such as Cursor (preferred), Claude Code, or Codex.
Experience governing AI ecosystems across multiple collaboration and productivity platforms.
Experience with OAuth, SSO, SCIM, delegated authorization, and enterprise identity patterns.
Certifications in cloud architecture, enterprise architecture, cybersecurity, or AI.

Responsibilities

Define enterprise AI platform architecture, standards, and guardrails aligned with the broader technology strategy.
Establish reference architectures, approved tooling, and reusable patterns for agents, retrieval, and orchestration.
Evaluate emerging AI technologies and recommend adoption, integration, and governance approaches.
Document architectural decisions that balance innovation, scalability, cost, and risk.
Translate business needs into production-ready AI solutions, including agents, assistants, RAG, and workflows.
Design agentic capabilities using function calling, MCP, model orchestration, memory, and grounding.
Guide teams hands-on from proof of concept through deployment and operationalization.
Ensure solutions follow established platform and engineering standards.
Architect integrations between AI platforms, enterprise applications, collaboration tools, and business systems.
Align AI solutions with the enterprise data ecosystem, using governed data that preserves quality and meaning.
Design secure APIs, connectors, and event-driven integrations that respect source-system permissions.
Partner with engineering teams to deliver reliable, scalable, and supportable integrations.
Define and enforce AI governance frameworks, policies, and operating standards.
Establish controls for model deployment, agent publishing, integration approval, and lifecycle management.
Partner with Security and Compliance on identity, access, data protection, and regulatory requirements.
Lead AI-specific risk assessments for new capabilities, integrations, and vendors.
Define standards for monitoring, observability, incident response, and platform support.
Establish evaluation methods for agent quality, safety, grounding accuracy, and production readiness.
Track platform health, adoption, and value realization through clear metrics and dashboards.
Serve as the senior escalation point for AI platform and integration issues.
Lead architecture reviews and communicate decisions clearly to technical and business audiences.
Coach engineers and architects, building a bench for future AI platform leadership.
Influence cross-functional priorities through technical expertise and pragmatic judgment.
Act as the go-to expert for enterprise AI architecture and platform engineering.