Job 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 What We re Looking For: 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 Additional Information Base Pay Range: 233,360.00 - 320,870.00 USD Annual This role may also be eligible for Equity Compensation and/or Bonus Incentive Compensation. Procore is committed to offering competitive, fair, and commensurate compensation. Actual compensation will be based on a candidate’s job-related skills, experience, education or training, and location. For Los Angeles County (unincorporated) Candidates: Procore will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable federal, state, and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. A criminal history may have a direct, adverse, and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: 1. appropriately managing, accessing, and handling confidential information including proprietary and trade secret information, as well as accessing Procore s information technology systems and platforms; 2. interacting with and occasionally having unsupervised contact with internal/external customers, stakeholders, and/or colleagues; and 3. exercising sound judgment.

Requirements

Must-haves

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
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
233,360.00 - 320,870.00 USD Annual

Nice-to-haves

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
Additional Information

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aillmmlapireacttypescriptnode.jspythonkubernetesci/cdawsgcpazure

Platform: workday
Effort: long