Job Description
This is a 100% remote position open only to candidates currently based in Canada. Applicants must be legally authorized to work in Canada and reside in the country.
About Point
✨ Real Impact, Real People: Our mission at Point is to make homeownership more valuable and accessible. Your work directly helps homeowners access their wealth, achieve financial flexibility, and realize life changing goals.
✨ Funding: With over $175M raised from top investors like Andreessen Horowitz, WestCap, Greylock, and Prudential, we’re scaling fast! You have the opportunity to join us at a pivotal stage.
✨ Game-changing Product: We’re building a category defining company in home equity. We’ve earned a 4.7 Trustpilot rating and an A+ from the BBB, a testament to the value we provide to our 20,000+ customers.
✨ Great Place to Work: Our employees love working here! We are a Certified Great Place to Work and a Fortune Best Workplaces in the Bay Area.
✨ Remote First Culture, Genuine Connection: Work from anywhere in Canada, while staying closely connected through virtual collaboration, team gatherings, and a people-first culture.
About the role
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.
Your 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
About you
- 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 have
- 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)
Compensation at Point will be determined by skills, experience, and geographic location.
- CAD 144,528 - 159,741
This does not include any other potential components of the compensation package, including equity, benefits, and perks outlined above. At the launch of each position, we benchmark compensation to the appropriate role and level utilizing competitive compensation data from various data sources as references. At the offer stage, we use the signal we received from our interviews, coupled with your experience, location, and other job-related factors, to determine final compensation.
Point is proud to be an equal-opportunity employer. We provide employment opportunities regardless of age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, veteran status, or any other protected class. Each individual at Point brings their own perspectives, work experiences, lifestyles, and cultures with them, and we believe that a more diverse team creates more innovative products, provides better services to customers, and helps us all grow and learn.
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