We’re looking for an AI Agent Solutions Architect for our Datagrid division to lead the design, customization, and deployment of intelligent agent systems in real-world customer environments.
This role is ideal for someone who thrives at the intersection of LLM architecture and customer implementation. You’ll design reusable agent frameworks, develop complex prompt strategies, and integrate our agents into customer workflows across enterprise ecosystems. You’ll work cross-functionally with product, engineering, and customer teams to deliver outcomes that scale.
This position will report to our Senior Manager, Customer Success Engineering and the location is Bay Area, San Francisco, CA only.
What you’ll do:Design modular, scalable AI agents that reason, take action, and communicate with users across channels.
Meet with and partner closely with customers to understand their use cases and tailor agent workflows to their systems, tools, and data.
Build and optimize multi-step agent chains using prompt engineering, tool integration, and memory/state handling.
Develop proof-of-concept deployments and iterate toward production-ready solutions with enterprise clients.
Integrate external APIs, databases, internal systems, and retrieval-augmented generation (RAG) pipelines into agent frameworks.
Work alongside ML engineers to define performance metrics and improve agent reliability and explainability.
Build internal tooling for prompt versioning, A/B testing, and agent performance feedback loops.
Contribute to reusable design patterns, internal documentation, and knowledge sharing for field-facing solutions.
3+ years in software engineering, ML development, or solutions architecture with 2 years working on LLMs or agentic systems.
Deep expertise in prompt engineering, agent orchestration, tool use, and stateful reasoning systems
Hands-on experience with frameworks like LangChain, AutoGen, Semantic Kernel, or similar.
Strong programming skills in Python and familiarity with APIs, webhooks, and AI infrastructure.
Experience deploying AI-driven systems in enterprise or production environments.
Familiarity with vector databases, embeddings, and RAG architecture.
Strong client communication skills and a passion for delivering AI that solves real problems
Bonus: Knowledge of symbolic reasoning, knowledge graphs, or multi-modal agents.
A technical problem solver who loves translating ambiguous goals into scalable AI systems.
A customer advocate who enjoys working directly with users to design meaningful solutions.
A builder who ships fast, learns on the fly, and iterates quickly.
A collaborator who bridges the gap between product vision and technical execution.
A startup-minded contributor who thrives in fast-moving, high-ownership environments.
If you thrive at the intersection of strategy, customer engagement, and data-driven success, we’d love to connect with you!
Additional InformationBase Pay Range:
103,960.00 - 142,945.00 USD AnnualThis 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.
