AI Enablement & DevOps Platform Lead

pointdigitalfinance

San Francisco (CA)

Hybrid

USD 270,000 - 298,000

Full time

6 days ago

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Job summary

Point is standing up a new AI Enablement function, and this dual-mandate leader will own it alongside our DevOps and platform practice.

You will run the reliability, delivery, and cloud foundations a lending business depends on, while building the central hub that partners with our corporate functions (HR, Legal, Compliance, Accounting, Finance) and our Operations team (underwriters, processors, closers) to automate and augment their work with AI.

Qualifications

10+ years in DevOps, platform, SRE, or infrastructure engineering.
3+ years leading and growing engineering teams.
Experience shipping AI automations to production, including LLM agents, tool calling, RAG, and workflow orchestration.
Production proficiency with infrastructure-as-code (Terraform), CI/CD, containerization (Docker, Kubernetes), and at least one major cloud (AWS, GCP, or Azure).
Excellent cross-functional communication, and the ability to earn trust with non-engineering stakeholders such as Legal, Compliance, Finance, and Operations.
Technical fluency to guide and review engineering and automation work (e.g., Python).

Responsibilities

Lead the infrastructure platform and shared-services organization, and drive key initiatives across the SRE and infrastructure functions.
Own reliability, CI/CD, infrastructure-as-code (Terraform), cloud platforms (AWS, GCP, Azure), containerization (Docker, Kubernetes), release tooling, and observability, including incident management and security and compliance (SOC 2).
Stand up and run AI Enablement as the central hub: the sanctioned platform, guardrails, reusable components, and the harder builds.
Partner with corporate functions and Operations to identify high-value workflows and design agentic AI solutions (LLM-based agents, tool calling, RAG, orchestration, and n8n / Zapier / custom integrations).
Partner closely with IT and Security to keep enablement safe and compliant, including sanctioned tooling, access, and data-handling boundaries for sensitive and regulated functions.
Drive adoption of what the team ships: define success metrics, baseline before building, and measure impact such as capacity reclaimed, cycle time, cost per loan, and stickiness.
Define multi-quarter roadmaps tied to measurable business outcomes.
Stay current on AI and automation advances, and pivot the roadmap based on user feedback and new technical capabilities.
Set technical and quality standards through architecture guidance and review.