Staff GTM AI Engineer

Procore Technologies; Bengaluru; On-site; INR 4,500,000 - 7,000,000; Full time

Job summary

Procore Technologies in Bengaluru seeks a Staff Engineer, GTM AI to join the India team. You will lead the technical strategy and implementation for our Go-to-Market AI systems, defining the architectural foundation for an enterprise-scale agentic solution that powers our sellers.

This high-visibility role demands systems thinking: own architecture across functions, design real-time data and AI infrastructure, and mentor engineers while building scalable, auditable outputs.

Qualifications

• 7–10+ years in software engineering with large‑scale distributed systems.
• Expert‑level Python and AWS cloud environments.
• Experience building on Agentic frameworks and with LLMs at scale.
• Mastery of Kubernetes, microservices and high‑throughput event‑driven architectures.

Responsibilities

• Architectural ownership of Seller Agentic platform; own long‑term health and scalability.
• Design next‑gen data/AI infrastructure, real‑time pipelines, and robust integration layers.
• Lead the data strategy to establish a single source of truth for account intelligence.
• Hands‑on leadership and mentorship; help ship code while elevating the team.

Skills

Python

AWS

Distributed systems

Event-driven

LLMs

Kubernetes

System architecture

Tools

LangGraph

Claude

Vertex AI

Workato

Job description

We are looking for a Staff Engineer, GTM AI to join the Procore India team. In the role you will lead the technical strategy and implementation for our Go-to-Market (GTM) AI systems. This is a high-visibility, "Staff+" role where you will not just contribute code—you will define the architectural foundation for our internal agentic solution. You will lead the transition from rapid experimentation to a scalable, production-grade agentic engine that empowers our sellers. If you are a systems‑thinker who thrives on scaling complex, event‑driven AI platforms and you want to define "how things are built" at an enterprise scale, this is your role.

Responsibilities

• Architectural Ownership
  • System Authority: Serve as the technical lead for our Seller Agentic platform. You own the architecture across business functions and are responsible for its long‑term health and scalability.
  • Platform Evolution: Design and build the next‑gen data/AI infrastructure. This includes robust integration layers, real‑time intelligence pipelines, and service architectures that handle high‑volume data without degradation.
  • Risk Mitigation: Anticipate scaling bottlenecks. You will define the roadmap for iterative modernization to ensure the platform is future‑proofed before performance issues surface
• Technical Execution & Mentorship
  • Hands‑on Leadership: While you are a strategic leader, you are also a practitioner. You will contribute to writing and shipping the code.
  • Engineering Excellence: Set the standards for the team. You will ensure that rapid prototyping is built on sound, sustainable foundations, teaching others how to manage complexity as the platform scales.
  • The "Golden Record" Strategy: Lead the data strategy to establish a single, trusted system of record for account intelligence, ensuring consistency across the revenue lifecycle.
• Engineering Outcomes You’ll Own
  • Scalable Architecture: Build a foundation that supports moving from one use case to dozens without regressions or downtime.
  • Systemic Trust: Ensure AI outputs are auditable, accurate, and consistent. You will turn "Trust" into a provable engineering metric, not a marketing claim.
  • Multiplier Effect: Your abstractions and API boundaries should enable junior engineers to ship faster and safer. You are here to amplify the team’s output.

Requirements

• Experience: 7–10+ years in software engineering, with a proven track record of owning large‑scale, distributed system architectures.
• Languages & Infra: Expert‑level fluency in Python and modern cloud environments (AWS).
• Agentic Platforms: Demonstrated experience building on Agentic frameworks (e.g., LangGraph, Claude, Vertex AI, Workato).
• AI/ML Ops: Deep understanding of LLMs, RAG, vector databases, memory systems, and prompt engineering at scale.
• Architecture: Mastery of Kubernetes, microservices, and high‑throughput event‑driven architectures.

Leadership & Soft Skills

• Security Mindset: Proven ability to build enterprise‑grade products with strict compliance, data privacy, and security‑first principles.
• Communication: A track record of translating complex technical trade‑offs into business‑aligned roadmaps for executive leadership.
• Mentorship: Experience guiding engineering teams through hyper‑growth or rapid scaling phases.

Nice to Have

• Experience with Revenue Tech / CRM (Salesforce,GONG, Outreach etc.) data structures.
• Exposure to AI Evaluation frameworks (automated testing/QA for LLM outputs).
• Experience working in a global-local model, driving alignment between distributed engineering teams.