• architect, implement, maintain, and optimize highly available and scalable cloud infrastructure primarily on AWS • develop, manage, and maintain scalable and reproducible cloud environments using Infrastructure as Code tools • design, implement, and optimize CI/CD pipelines using tools such as GitLab CI/CD, Argo CD, Jenkins, or CircleCI • manage and operate containerized applications using Docker and Kubernetes • implement and maintain monitoring, logging, and alerting systems using tools such as Datadog, CloudWatch, Prometheus, Grafana, or ELK Stack • implement cloud security best practices • manage and optimize Amazon RDS database infrastructure • configure and administer Cloudflare to enhance network security • collaborate with development, product, and operations teams

• Own executive relationships across a portfolio of strategic enterprise accounts; serve as the single point of accountability for client outcomes, satisfaction, and growth. • Co-develop and execute account strategies that expand Valiantys' footprint across SDLC tooling (Atlassian, GitHub/GitLab), AI-enabled delivery, DevOps, and cloud infrastructure. • Lead solutioning for complex pursuits — partnering internally to scope DevOps, platform engineering, and AI-augmented SDLC engagements. • Shape and communicate target architectures spanning CI/CD, security, compliance, resilience, and AI copilots integrated into the delivery lifecycle. • Govern delivery quality in partnership with engagement managers; intervene on escalations and ensure architectural integrity. • Represent Valiantys in executive briefings, QBRs, industry events, and joint go-to-market activities. • Mentor consultants and architects, contributing to Valiantys' practice development in AI-enabled SDLC and DevOps.

• Strengthen the Recorded Future product team

Role Description 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: - 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. Qualifications - 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). Requirements - 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 - 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. - 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. Company Description - Real Impact, Real People: Our mission at Point is to make homeownership more valuable and accessible. - Funding: With over $175M raised from top investors like Andreessen Horowitz, WestCap, Greylock, and Prudential, we’re scaling fast! - Game-changing Product: We're building a category-defining company in home equity, with a 4.7 Trustpilot rating and an A+ from the BBB. - Great Place to Work: 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.