Sr. Software Engineer - CloudOps

• Solid experience implementing and operating high performance, high availability, reliable, and secure systems. 

• Experience designing and developing solutions using AWS services such as: Lambda, API Gateway, S3, DynamoDB, RDS, KMS, Kinesis, Route 53, IAM, CodeBuild, CodePipeline, and other managed services. 

• Experience with cloud automation and IaC tools such as AWS CloudFormation, AWS CDK, Terraform, etc. 

• Track record of reducing operational toil by moving beyond one-off automation toward guardrailed, AI-driven self-service - where IaC is the trusted substrate and AI-assisted interfaces let users and agents safely resolve their own requests. 

• Proficiency using AI-assisted engineering tools (e.g., Claude Code, Amazon Q, Copilot) to accelerate development, troubleshooting, and automation - with the depth to review AI-generated output critically and understand why a change is correct before shipping it. 

• Comfort operating in ambiguity - making pragmatic decisions and moving work forward without full clarity, learning through delivery rather than waiting for a perfect spec. 

• Familiarity with GenAI/agent services (Amazon Bedrock, Strands, AgentCore, or comparable) and the fundamentals of securing model access (IAM, KMS) and managing cost and quotas - preferred. 

• Experience with multi-account AWS governance (Control Tower / Landing Zone Accelerator) preferred. 

• Strong written and communication skills. 

• Experience in hybrid on-prem and cloud implementation and integration preferred. 

• Good understanding of Web and API development and implementation concepts. 

• Experience working with serverless and container technologies. 

• Experience with agile methodologies. 

Responsibilities 

• Enable engineering teams - provide the platforms, tooling, guardrails, and support that let them ship faster and more safely, reducing their dependence on manual, ticket-driven help. 

• Advance the support model up the automation curve - progress manual, repetitive support toward automation and AI-driven self-service, so common requests resolve themselves with the right approvals and controls in place. 

• Lead projects end to end - from problem definition and design through implementation, deployment, and iteration - driving them to completion independently. 

• Drive technical decisions and improvements across the codebase and infrastructure, building alignment with partner teams to move change forward without relying on formal authority. 

• Own secure design and operations - build with least-privilege and defense-in-depth, and drive remediation of security findings to closure. 

• Partner with feature teams to understand their operational needs, and with the AIops and AI Platform teams to adopt their capabilities in CloudOps workflows rather than duplicating platform work - channeling requirements and feedback in both directions. 

• Can work across the stack from frontend to backend for the components involved, with strong ownership of cloud infrastructure and automation. 

• Design and develop advanced software and cloud solutions; review, analyze, and resolve application and production issues as needed. 

• Use AI-assisted tooling to accelerate design, coding, and troubleshooting - applying engineering judgment and system knowledge to validate, correct, and improve what AI produces rather than accepting it as-is. 

• Set a strong bar for code quality, testing, and maintainability, and raise it through example and code review. 

• Build and operate CI/CD and testing as first-class engineering - automated pipelines, quality gates, and AI-assisted test generation and review - and raise the team's practices by example rather than by manual hand-holding. 

• Participate fully in weekly iterations, pulling work from a Kanban board and driving stories to "Done" as a team. 

• Identify risks early, surface them clearly, and unblock work to keep delivery moving. 

• Create strong working relationships with inter-department teams and partners to deliver the best solutions possible. 

• Continuously learn and keep up to date with emerging cloud and AI technologies to evaluate impact to business and member value. 

• Participate and provide feedback during planning meetings (i.e., pre-iteration, iteration, and retrospectives). 

• Perform all other duties as assigned. 

Education 

• Four-year college degree in Computer Science or equivalent combination of education and work experience required. 

Why This Role Matters 

CloudOps is the foundation the feature and platform teams build on. You'll enable the teams delivering AI-enabled solutions, self-service portals, identity, sales and payment functions, and much in between - giving them the platforms, pipelines, and guardrails to ship safely and fast. Your work has an immediate impact on the ease of use for our members.