Root Cause Ownership: Independently diagnose complex workflow failures, platform anomalies, and system behavior using logs, database investigation, API testing, and other available technical resources.

High-Fidelity Escalation: Provide Engineering teams with rigorous, data-backed investigation results, reproduction steps, logs, technical context, and clearly defined requests for assistance.

Proactive Deep Dives: Investigate beyond surface-level symptoms to identify potential root causes and recurring patterns before issues are escalated or resolved.

System Investigation: Navigate application behavior, source code, logs, APIs, and database data to correlate symptoms across systems.

Deployment Awareness: Collaborate with Engineering to understand deployments, architectural changes, dependencies, and potential downstream impacts.

Autonomous Execution: Operate with minimal day-to-day supervision while effectively prioritizing high-volume operational work alongside longer-term initiatives.

Queue Integrity: Maintain strong ownership of the team's operational queue, ensuring issues have clear owners, current documentation, and defined paths toward resolution.

End-to-End Ownership: Drive assigned issues from initial investigation through resolution, escalation, or handoff while maintaining appropriate stakeholder communication.

Process Improvement: Identify and implement small-scale process or tooling improvements that reduce friction for PET, Engineering, and stakeholders.

Strategic Friction Reduction: Recognize recurring issue patterns and surface larger platform or operational problems to leadership with supporting data and business impact.

Serve as a technical liaison between client-facing teams, Product, Engineering, and other stakeholders.

Use AWS services, logs, and platform resources as part of independently investigating and diagnosing complex technical issues.

Proactive Communication: Proactively communicate issue status, technical findings, blockers, business impact, and next steps to stakeholders and partner teams without requiring follow-up.

Translate complex technical problems into clear business impact and actionable next steps.

Facilitate cross-functional technical discussions when multiple teams are required to resolve an issue.

Produce clear post-incident or issue summaries describing symptoms, investigation, impact, findings, and resolution.

Maintain high-quality technical documentation, troubleshooting workflows, and decision trees that enable others to resolve similar issues independently.

Actively participate in team troubleshooting and collaborate with peers before escalating issues.

Help less-experienced engineers develop stronger investigative and troubleshooting skills by explaining the how and why, rather than simply providing answers.

Share technical discoveries, SQL queries, troubleshooting techniques, and investigation patterns with the broader team.

Use GenAI tools to accelerate log analysis, understand code behavior, develop queries or scripts, and produce high-quality technical documentation.

Identify opportunities where AI or automation can reduce repetitive operational work and improve team efficiency.

2–5 years of relevant experience in technical support engineering, platform enablement, software engineering, DevOps, production support, or another deep technical troubleshooting role.

Strong troubleshooting skills using observability and log-analysis platforms such as Datadog or Observe.

Experience troubleshooting applications and services operating within AWS cloud environments.

Experience investigating data using complex SQL queries.

Ability to manually test APIs using tools such as Postman or cURL, validate JSON payloads, and diagnose failures using browser developer tools.

Ability to navigate source code and application logic sufficiently to correlate user-facing behavior with backend logs and system behavior.

Demonstrated ability to independently investigate complex technical issues and manage competing priorities.

Strong written and verbal communication skills, including the ability to translate technical problems into business impact.

Experience using GenAI tools such as GitHub Copilot, Gemini, Claude, or similar tools to assist with technical investigation, scripting, documentation, or information discovery.

Experience developing scripts or advanced queries to aggregate data or automate repetitive operational tasks.

Experience investigating RBAC, permissions, authentication, or authorization-related failures.

Experience supporting high-stakes client onboarding, production incidents, or critical business workflows.

Working knowledge of one or more programming or scripting languages.

Strong SQL skills and familiarity with application and database architecture.

Experience creating technical runbooks, troubleshooting guides, or operational documentation.