DevOps Engineer (Engineering Productivity & Tooling)

About the position Point is transforming homeownership through innovative financial products — and we're doing it with an engineering organization that's going AI-native. We're looking for a Senior DevOps Engineer to sit at the center of that transformation: building internal tooling to measure and accelerate engineering productivity, ensuring the availability and reliability of our business systems, and eliminating friction across our Secure SDLC.

Responsibilities

• Build and maintain internal developer productivity tooling — dashboards, metrics, and measurement frameworks that surface engineering throughput, cycle time, and quality signals
• Instrument token consumption and model cost across agentic workflows (task type, epic, user) to provide visibility and support cost optimization as we scale AI coding agent usage
• Establish availability monitoring and alerting across all business systems and internal applications, and develop SOPs for detecting and responding to disruptions
• Identify and reduce friction across the Secure SDLC — streamlining SAST/DAST integration, compliance tooling, and security scanning so engineers can ship fast without cutting corners
• Manage, scale, and improve AWS cloud infrastructure to support reliable and secure production systems
• Build, operate, and continuously improve CI/CD pipelines using GitHub Actions to enable fast, safe, and repeatable deployments
• Develop and maintain Infrastructure as Code (Terraform) for consistent, auditable, and scalable environments
• Evaluate and optimize AI model hosting on AWS Bedrock — including model selection, performance benchmarking, and cost trade-offs across providers
• Drive adoption and standardization of AI coding agent tooling (Claude Code, Cursor) across engineering teams, and evaluate emerging tools as the ecosystem evolves
• Partner with Security to deploy and operate SAST, DAST, and SIEM solutions as part of our Secure SDLC

Requirements

• 5+ years of experience in Platform Engineering, DevOps, or Cloud Engineering; Bachelor's or Master's in Computer Science, Engineering, or a related technical field
• Demonstrated experience building internal developer productivity tools and metrics systems (e.g., DORA metrics, cycle time, deployment frequency, engineering throughput)
• Strong proficiency in at least one programming language (Python, Go, TypeScript, or similar) for building automation and internal tooling
• Practical experience using AI coding agents (Claude Code, Cursor, GitHub Copilot, or similar) as part of your own engineering workflow
• Hands-on experience with AWS services including compute (ECS, EKS, EC2, Lambda), storage (S3), data (RDS, Redis), and governance and identity (Control Tower, IAM)
• Hands-on experience building and maintaining CI/CD workflows using GitHub Actions
• Solid experience with Infrastructure as Code using Terraform or similar tools (AWS CDK, CloudFormation)

Nice-to-haves

• Experience managing or evaluating LLM hosting platforms such as AWS Bedrock — including model selection, token cost optimization, and multi-model evaluation frameworks
• Experience building tooling to support agentic or multi-agent AI workflows (session tracking, cost attribution, observability)

Benefits

• equity
• benefits
• perks

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