Staff GTM AI Engineer

Overview

Lead the technical strategy and implementation for Procore's Go-to-Market AI systems. Define the architectural foundation for an internal agentic solution and lead its transition from rapid experimentation to a scalable, production-grade agentic engine for sellers.

What you'll do

• Serve as the technical lead for the Seller Agentic platform.
• Own the architecture across business functions and its long-term health and scalability.
• Design and build next-generation data and AI infrastructure, including integration layers, real-time intelligence pipelines and service architectures for high-volume data.
• Anticipate scaling bottlenecks and define the roadmap for iterative modernization before performance issues surface.
• Contribute to writing and shipping code.
• Set engineering standards and ensure rapid prototypes are built on sound, sustainable foundations.
• Teach others how to manage complexity as the platform scales.
• Lead the data strategy for a single, trusted system of record for account intelligence across the revenue lifecycle.
• Build a foundation that supports moving from one use case to dozens without regressions or downtime.
• Ensure AI outputs are auditable, accurate and consistent.
• Develop abstractions and API boundaries that enable junior engineers to ship faster and safer.

What you'll need

• 7–10+ years in software engineering.
• A proven track record of owning large-scale, distributed system architectures.
• Expert-level fluency in Python.
• Expert-level fluency in modern cloud environments, including AWS.
• Demonstrated experience building on agentic frameworks, such as LangGraph, Claude, Vertex AI or Workato.
• Deep understanding of LLMs, RAG, vector databases, memory systems and prompt engineering at scale.
• Mastery of Kubernetes, microservices and high-throughput event-driven architectures.
• Proven ability to build enterprise-grade products with strict compliance, data privacy and security-first principles.
• A track record of translating complex technical trade-offs into business-aligned roadmaps for executive leadership.
• Experience guiding engineering teams through hyper-growth or rapid scaling phases.

Nice to have

• Experience with Revenue Tech or CRM data structures, such as Salesforce, GONG or Outreach.
• Exposure to AI evaluation frameworks for automated testing and QA of LLM outputs.
• Experience working in a global-local model and driving alignment between distributed engineering teams.

Details

• Location: Bangalore, India.