Software Engineering SMTS - Cloud Reliability

Description

The company's Cloud Platform Engineering team builds and runs the highly available, active-active cloud infrastructure that supports the business at scale.

The team treats its internal platform as a product, focusing on developer speed, automation first design and no ticket-based operations.

It is a small group at the front edge of platform engineering, using AI tools in every workflow, a chat platform as its enterprise hub and agents connected to its GitOps pipelines. It moves fast and automates heavily.

Team members are T-shaped engineers with distinct focus areas who learn from each other. All share a commitment to treating internal engineers as customers, removing toil by automating it, building security into code from the start, engineering for failure with a 99.999% availability target, building deep observability with telemetry, tracing and automated alerting, and making AI and agents part of every workflow and pipeline.

You will build the infrastructure engine: design and ship infrastructure vending machines and reusable IaC modules so internal product teams can provision governed, multi-account AWS environments in 15 minutes instead of two weeks.

Applicants are asked to apply for no more than 3 roles within 12 months.

Responsibilities

• Own AFT as the Terraform subject matter expert and automate multi-region, multi-account provisioning through AWS Organizations and Control Tower.
• Write, test and version a library of secure, pre-approved Terraform modules, and turn compliance needs into Sentinel and SCP policies.
• Build automated security scanning, policy-as-code checks and cost guardrails into developer pull requests, using AI to flag risk, suggest fixes and keep the rules current.
• Set up automated failover across availability zones and regions with Cloud WAN, ARC and FIS, and run Game Days that simulate major failures.
• Connect provisioning pipelines and AI agents to chat for live insight, chat-based control and zero-touch operations.
• Use AI coding assistants (Claude Code, Codex, Cursor) as your main tools to write, review and validate infrastructure code quickly.
• Build central logging, metrics and tracing with Prometheus, Grafana, ELK and Datadog, and define and enforce SLOs and SLIs.
• Advise internal teams on observability practice, alerting and resilience architecture as a trusted advisor, not as a CloudOps function.

Requirements

• 7+ years in software engineering, SRE or platform engineering in large-scale AWS environments.
• Expert Terraform skills: state at scale, decoupled modules and continuous IaC delivery.
• Strong Python or Go for custom tooling and AWS SDK work (Boto3 or Go SDK).
• Deep knowledge of IAM, VPC, Cloud WAN, EKS/ECS, Lambda and DynamoDB, including multi-region active-active DR.
• Experience with GitOps deployments that have automated guardrails built into enterprise pipelines.
• Daily use of AI-assisted development tools (Claude Code, Codex, Cursor, Gemini or equivalent).
• Preferred: AWS certifications such as Solutions Architect Professional, DevOps Engineer Professional or Security Specialty.
• Preferred: experience with AWS Control Tower, Account Factory for Terraform (AFT) or custom account vending.
• Preferred: hands-on chaos engineering with AWS FIS, Gremlin or equivalent Game Day experience.
• Preferred: experience building agentic pipelines or AI-integrated developer tooling.
• Preferred: familiarity with Slack platform development, Bolt SDK or ChatOps automation.
• Preferred: background in FinOps, Policy-as-Code (Sentinel, OPA) or secrets management (Vault).
• You automate recurring issues yourself and ship code instead of filing tickets.
• You take full ownership of your domain end to end, with no hand-offs.
• You spot single points of failure early and question unnecessary complexity.
• You keep runbooks, ADRs and processes in the repo, always current.
• You connect tools to remove toil and have clear views on how AI improves platform engineering.
• You work from chat, automate through it and build for agent-driven work.

Benefits

• The company offers benefits and resources to help you find balance and do your best work.
• AI agents are meant to speed up your impact.