Senior Platform Engineer
Weight Watchers
| Company | Weight Watchers |
| Category | Engineering |
| Location | United States - Remote |
| Remote | Remote |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 6 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
WeightWatchers is a global digital health company.
WeightWatchers is a global digital health company and the world’s #1 doctor-recommended, clinically studied behavioral weight health program. For sixty years, we have led the industry by blending science and community to help millions of people build sustainable healthy habits.
As the science of weight health rapidly evolves, so does WeightWatchers. We are redefining the category by developing new clinical pathways for GLP-1 medication access , creating specialized behavioral programs for members on weight-loss medications, and integrating medical care with our proven habit-change framework. By combining these clinical breakthroughs with our digital-first community, we are uniquely positioned to lead the future of weight health care. The Opportunity
We're expanding our Platform Engineering team to build out observability and incident response from the ground up. We have a cloud architecture supporting hundreds of services, but our visibility into system health, performance, and failures is largely manual today. We need someone who can architect and implement a modern observability stack—not just monitor it.
This is a chance to make an immediate impact: you'll design logging, metrics, and tracing patterns that the entire engineering organization depends on. You'll reduce toil, surface actionable signals, and turn chaos into clarity.
You'll report to our Head of Platform Engineering as an individual contributor and will have the autonomy to move quickly, make opinionated decisions, and set standards for how we operate.
What Success Looks Like
Phase 1: Audit & Plan – Map current gaps, propose tooling & rollout strategy, get buy-in.
Phase 2: Foundation – Select tools, document decisions, pilot agents on 2-3 services.
Phase 3: Standardize – Structured logging patterns, baseline dashboards, incident routing, alerting.
Phase 4: Prove It – Demonstrate reduced MTTD and MTTR, fewer manual escalations, documented runbooks, team trained on tooling.
Key Responsibilities
Observability Architecture & Implementation
Design and deploy a logging, metrics, and APM stack that scales with the organization
Establish agent configuration best practices (New Relic, OpenTelemetry, or alternatives)
Create structured logging patterns and cardinality management strategy
Implement distributed tracing to understand latency and failure paths across services
Incident Management & Response
Evaluate and select incident management platform (we're not locked into any vendor)
Build alerting policies that surface real signals without drowning teams in noise
Develop incident triage, escalation, and communication workflows
Create runbooks and post-incident analysis templates
Automation & Toil Reduction
Identify manual work in today's incident response and automate it away
Build dashboards, alerts, and self-service tools so teams don't need platform team involvement for basic troubleshooting
Codify monitoring and alerting as infrastructure (IaC)
Technical Leadership
Set SRE practices and standards for the organization
Mentor Platform Engineering team on observability concepts and tooling
Drive adoption: make it easy for service owners to instrument their code correctly
About You
Required
5+ years in SRE, platform engineering, or similar infrastructure role
Deep expertise in at least one observability domain (metrics, logging, tracing, or APM)
Experience with agent configuration and instrumentation (New Relic, Datadog, OpenTelemetry, or equivalent)
Track record of building (not just maintaining) monitoring/alerting systems
Comfortable making opinionated architectural decisions with incomplete information
Strong systems thinking—you understand tradeoffs between managed vs. open-source, complexity vs. coverage
Strongly Preferred
AWS and containerized env
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