Live opening · Posted 7 hours ago

Lead Site Reliability Engineer - Allergan Aesthetics

AbbVie · Seattle, WA, United States
Smartrecruiters Yes Full-time
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At a glance

The key details from the original listing.

Posted 7 hours ago
CompanyAbbVie
LocationSeattle, WA, United States
Job typeFull-time
Work modeYes
SkillsPython, AWS, Kubernetes, Terraform
SourceSmartrecruiters
ListedPosted 7 hours ago

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About the role

Description supplied by the original job listing.

The Lead Site Reliability Engineer will continuously collaborate with key stakeholders across the business to solve critical technical problems for Allergan Aesthetics. You will be a hands-on technical leader driving reliability, availability, and operational excellence for large-scale public-facing software. As part of the Cloud Platform team, you will own how we measure, protect, and improve production reliability — championing SRE practices, building resilience into our platform, and ensuring our services meet the availability and performance standards our customers expect. You will provide technical thought leadership, mentor engineers across the organization, and turn small ideas into high-fidelity technical game plans that achieve both reliability and business goals.
Reliability Engineering:
Define and champion SLO/SLI frameworks and error budget-based decision making to drive prioritization between reliability and feature work.
Own observability strategy across services — metrics, logs, traces, and alerting — ensuring signals are actionable and tied to user impact.
Lead capacity planning, load testing, and resilience/chaos testing for critical public-facing services.
Establish production readiness reviews and partner with development teams to improve services through rigorous testing and release procedures.
Identify and eliminate toil through automation, self-healing systems, and improved observability.
Gather and analyze metrics from operating systems and applications to drive performance tuning and fault finding.
Contribute reliability improvements to the platform through infrastructure-as-code (Terraform) and Kubernetes configuration, working within Cloud Platform team standards.
Incident Management & Response:
Own and evolve the incident response process, including severity definitions, escalation paths, and postmortem practice.
Participate in on-call rotations and provide hands-on support during incidents with appropriate urgency.
Troubleshoot and resolve infrastructure and application issues, driving blameless root cause analysis and tracking corrective actions to completion.
Standards & Architecture:
Champion reliability, scalability, and security standards across AA Tech services and the AA Tech product platform.
Partner and inform strategic architecture decisions for new services and major platform changes for reliability risks (failure modes, redundancy, scaling limits, alerting) before launch as part of Cloud Platform design reviews.
Define and maintain reliability standards (e.g., SLO coverage, alerting, runbooks, backup and recovery requirements) and track how services meet them
Stay current with the latest trends in site/service reliability practices and tooling. Identify proven technologies and solutions for emerging challenges.
Technical Mentorship:
Provide technical mentorship and guidance to senior-level DevOps and Software Engineers utilizing proven design patterns and experience building large-scale public-facing software.
Foster a culture of operational excellence, knowledge sharing, and continuous learning across the engineering organization.
Provide technical thought leadership to implement strategic architecture, systems, and projects on the roadmap.
Proven track record running SLO/error budget programs and incident management for large-scale production systems.
Deep experience with observability platforms (e.g., Datadog) and alert design.
Working proficiency with Terraform and Kubernetes on AWS; comfortable reading, reviewing, and contributing infrastructure code.
Strong scripting/programming skills (e.g., Python, Go) for automation and tooling.
Preferred:
Hands-on experience using or building agentic AI tools (e.g., Claude Code, MCP-based integrations) to automate engineering or operational workflows, with appropriate guardrails and human oversight.

Employment type
Full-time

Work arrangement
Yes

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