Staff GTM AI Engineer
procore · IN - India - Bangalore ·
- Seniority
- Staff
- Category
- AI engineering
- Experience
- 10+ years
- Company size
- 1000+
procore · IN - India - Bangalore ·
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.