> Markdown version of [/jobs/ext/2050072-ai-application-architect](https://www.wearedevelopers.com/jobs/ext/2050072-ai-application-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Application Architect - **Company:** Procore - **Location:** West, TX, United States - **Experience:** Expert - **Salary:** $233,360.0 - $320,870.0 - **Contract:** Permanent contract - **Skills:** Kubernetes Security, Artificial Intelligence, Airflow, Amazon Web Services, Audit Trail, Microsoft Azure, Software as a Service, Continuous Integration, Cross-Site Request Forgery, Programming Tools, Python (Programming Language), Key Management, Machine Learning, Node.Js, OAuth, Open Source Technology, Productivity Software, Role-Based Access Control, Zero Trust Network Access, Software Engineering, Strategies of Testing, TypeScript, Management of Software Versions, Web Applications, Workflow Management Systems, Enterprise Software Applications, ReactJS, Large Language Models, Multi-Agent Systems, Software Security, Backend, Rate Limiting, AI Platforms, Kubernetes, Machine Learning Operations, Front End Software Development, Api Design, Data Pipelines, User Administration - **Published:** August 14, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17949514?backUrl=%2Fcareer%2F17949514%2FAi-Application-Architect-Texas-Austin ## About the Role * 10+ years of software engineering with 5+ years in a principal/staff or architect-level role * Hands-on experience designing and shipping production LLM-powered applications (not just prototypes) * Experience shipping complex, user-facing application platforms - particularly in SaaS, productivity tools, or enterprise software. * Demonstrated ability to lead full-stack teams building rich web application experiences (React, TypeScript/Node.js, modern frontend architectures) with strong backend (Python) and API design sensibility * Deep understanding of enterprise requirements: User Management, RBAC/ABAC permission models, audit logging, compliance frameworks, multi-tenant governance, and admin tooling. * Experience building contextual or adaptive UX - applications that respond to user state, workflow context, or personalization signals. * Strong grasp of cloud-native architecture (Kubernetes, Helm, container security, CI/CD) on AWS, GCP, or Azure * Solid understanding of API security: OAuth2, CSRF, rate limiting, secrets management, and zero-trust principles applied to AI endpoints Preferred Experience: * Experience with MCP (Model Context Protocol) or comparable tool-calling/plugin infrastructure * Familiarity with workflow orchestration engines (Temporal, Prefect) for long-running AI tasks * Exposure to LLM evaluation frameworks (automated judging, red-teaming, regression suites) * Background in developer-facing products or internal AI platforms / AI coding tooling * Understanding of supply chain security for ML models (artifact signing, registry enforcement, SBOM) * Contributions to open-source AI tooling or published architectural writing ## Description We are looking for an experienced AI Application Architect to lead the technical design and evolution of our AI-powered product suite. You will be the technical authority on how we build, scale, and secure AI-native applications - spanning agent orchestration, LLM infrastructure, data pipelines, and developer tooling. You'll work closely with engineering leads, product managers, and ML practitioners to translate ambitious AI capabilities into robust, production-grade systems. What You'll Do: * Define architecture for AI-native applications including agentic systems, RAG pipelines, multi-model inference layers, and human-in-the-loop workflows * Drive infrastructure decisions for scalable AI workloads: vector databases (Turbopuffer, pgvector, Milvus), workflow orchestration (Temporal, Airflow), and async compute patterns * Design and govern the integration layer between LLMs (OpenAI, Anthropic, Gemini, open-source) and backend services, including prompt management, context window optimization, and cost governance * Lead LLMOps and observability strategy - tracing (OpenTelemetry), evaluation pipelines, prompt versioning, drift detection, and integration with platforms like Langfuse or Arize * Establish security and compliance posture for AI systems - SSRF/injection hardening, LLM guardrails, data residency, and supply chain security for model artifacts and dependencies * Partner with product and research to evaluate emerging AI capabilities and determine when/how to adopt them (e.g., reasoning models, multimodal, fine-tuning, RLHF) * Champion engineering standards - API design, schema governance, testing strategies, and architecture decision records (ADRs) * Mentor senior engineers and establish guild-level technical communities around AI platform topics ## Related Videos - [Bringing the power of AI to your application.](https://www.wearedevelopers.com/videos/1010-bringing-the-power-of-ai-to-your-application) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Watch Tests Go Brrrr! : Getting Started with Cypress in ReactJS](https://www.wearedevelopers.com/videos/282-watch-tests-go-brrrr-getting-started-with-cypress-in-reactjs) - [Keeping applications secure by evolving OAuth 2.0 and OpenID Connect](https://www.wearedevelopers.com/videos/100152-keeping-applications-secure-by-evolving-oauth-2-0-and-openid-connect) - [One AI API to Power Them All](https://www.wearedevelopers.com/videos/1601-one-ai-api-to-power-them-all) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j)