• 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

• Backend Development: Build, optimize, and maintain core Django services and APIs. • System Architecture: Design scalable, secure solutions to support marketplace growth. • Code Quality: Conduct code reviews and uphold engineering best practices and standards. • Data Management: Work with Postgres and other data systems to ensure accuracy and performance. • Cross-Pod Support: Collaborate with other pods and contribute to occasional frontend needs. • Issue Resolution: Investigate, debug, and resolve platform bugs and performance bottlenecks. • Team Collaboration: Participate in standups, planning, and alignment with Product and QA.

• Own the deployment, IaC, observability, runtime management and cost governance across all layers of the Agentic Platform. • Build IaC with Terraform or AWS CDK. • Implement CI/CD (CodePipeline, GitHub Actions, GitLab CI). • Configure CloudWatch and OpenTelemetry for LLM observability. • Manage environment isolation and prompt/model versioning. • Implement containerization with Docker, ECS Fargate, or EKS. • Track platform costs using CloudWatch budgets.