• Set the example in driving individual user stories to completion from start to finish • Assess and identify risks that may be present to achieving the team’s larger goals • Document best practices and strategies regarding application deployment and infrastructure construction • Work in tandem with our platform and software engineering teams and leaders to identify and implement optimal cloud-based solutions for the company • Drive implementation of functionally appropriate and technically sound solutions meeting all quality & security standards • Assist the team in achieving ambitious goals, providing regular feedback, and driving continuous improvement • Participate in all aspects of our software development lifecycle for cloud-based solutions, including planning, defining requirements, developing, testing, and deploying those solutions with the team

• Set the example in driving individual user stories to completion from start to finish • Assess and identify risks that may be present to achieving the team’s larger goals • Document best practices and strategies regarding application deployment and infrastructure construction • Work in tandem with our platform and software engineering teams and leaders to identify and implement optimal cloud-based solutions for the company • Drive implementation of functionally appropriate and technically sound solutions meeting all quality & security standards • Assist the team in achieving ambitious goals, providing regular feedback, and driving continuous improvement • Participate in all aspects of our software development lifecycle for cloud-based solutions, including planning, defining requirements, developing, testing, and deploying those solutions with the team

• Design, prototype and productionize scalable AI/machine learning models • Play a critical in setting up the best practices in machine learning, setting direction of the machine learning platform • Develop frameworks, pipelines, libraries, utilities and tools that process massive data for ML tasks • Partner with ML engineers and data scientists to troubleshoot and optimize complex ML pipelines • Work with product managers and business partners to gather requirements for machine learning models • Build model deployment platform that can simplify implementing new models • Build end-to-end reusable pipelines from data acquisition to model output delivery • Mentor and guide junior data scientists to deploy their models into production • Design & Build ML (engineering) solutions that unlock new ML modeling capabilities for BetterHelp

• Build and maintain CI/CD pipelines and deployment automation to support continuous, high-quality software delivery • Provision and manage cloud infrastructure using Terraform, keeping things scalable, secure, and well-documented • Partner with product engineering teams to design resilient, cloud-native solutions and review code for quality and standards adherence • Monitor, troubleshoot, and improve platform performance and availability — including on-call coverage when needed • Embed security best practices into platform design, from access controls and encryption through to deployment pipelines • Contribute to platform architecture decisions and help evolve our infrastructure as the product and team scale • Write and maintain technical documentation: architecture diagrams, runbooks, and infrastructure standards