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Tech Stack
Tools & technologiesCloudDistributed SystemsDNSElasticSearchPHPSQL
About the role
Key responsibilities & impact- Investigate technical issues reported by enterprise customers and determine root causes
- Use Datadog logs, traces, metrics, and dashboards to diagnose issues across distributed services
- Read code across multiple repositories to verify hypotheses and trace request flows
- Query databases to confirm system state and reproduce issues
- Manage support tickets through intake, resolution, and the support-to-engineering escalation chain
- Communicate proactively with enterprise customers through structured updates, clear next steps, and expectation management
- Partner with engineering teams during escalations by framing issues, providing reproducible evidence, and advocating for customer impact
- Document findings, contribute to internal knowledge bases, and identify recurring patterns for systemic improvements
- Participate in rotational on-call coverage for high-severity incidents during evenings and weekends
- Own a technical domain within the platform and serve as the team reference point
- Develop and maintain investigation playbooks, runbooks, escalation paths, and knowledge-base content
- Analyze recurring failure patterns and advocate for customer-impacting platform fixes
- Evaluate and apply AI tooling to daily work and share effective approaches with the team
- Support onboarding of new team members and improve technical investigation and customer communication standards
Requirements
What you’ll need- 5+ years of hands-on technical support or systems engineering in a complex B2B SaaS or enterprise environment
- Proven experience supporting enterprise (B2B) customers, ideally in a SaaS or cloud-based product environment
- Experience improving support-team operations through documentation, playbooks, processes, and quality standards
- Experience supporting or mentoring less experienced colleagues
- Comfortable reading server-side code in at least one language to trace logic and verify code paths
- Hands-on experience with observability and central logging tooling; Datadog preferred
- Familiarity with Kibana, OpenSearch, Elasticsearch, or similar central logging platforms is a strong plus
- Comfortable searching logs, reading distributed traces, and querying metrics
- Solid SQL skills, including querying relational databases to verify system state, reproduce issues, and understand data models
- Working knowledge of distributed systems concepts, including asynchronous and synchronous communication, queues, retries, idempotency, and eventual consistency
- Comfort with HTTP and API debugging, including curl, response headers, status codes, basic DNS, REST, and webhook flows
- Familiarity with cloud-based, multi-tenant SaaS architectures; understanding tenant isolation and configuration delivery is a strong advantage
- Hands-on AI tooling experience beyond chat interfaces, such as building an agent, automating a workflow, using an API, or serious experimentation
- Experience reading PHP is a nice-to-have
- Experience in e-commerce or digital commerce platforms is a nice-to-have
- Prior incident management or major-incident response experience is a nice-to-have
- Familiarity with PSP integrations, OMS, PIM, or search platforms is a nice-to-have
Benefits
Comp & perks- Remote work options
- Rotational on-call coverage for high-severity incidents (evenings, weekends)
- Confidential handling of personal information according to EEO guidelines
- Benefits/perks available via the company benefits page (may vary depending on location)