Job Description- Investigate technical issues reported by enterprise customers - analyse symptoms, form hypotheses, follow the evidence to the root cause
- Use observability tooling (Datadog logs, traces, metrics, dashboards) to diagnose issues across distributed services
- Read code across multiple repositories to verify hypotheses and trace request flows
- Query databases when needed to confirm system state and reproduce issues
- Manage tickets through their full lifecycle, from intake to resolution, across the support engineering escalation chain
- Communicate proactively and professionally with enterprise customers: structured updates, clear next steps, calibrated expectation management
- Partner with engineering teams when escalation is needed - frame issues clearly, provide reproducible evidence, advocate for customer impact
- Document findings, contribute to internal knowledge bases, and surface recurring patterns to drive systemic improvements
- Participate in rotational on-call coverage for high-severity incidents (evenings, weekends), supporting our enterprise customers when issues cannot wait until business hours
- Take ownership of a technical domain within the platform and act as the reference point for the team in that area
- Develop and maintain investigation playbooks, runbooks, escalation paths, and knowledge base content the team relies on
- Analyse recurring failure patterns to drive platform improvements, and advocate for customer-impacting fixes by framing systemic risk and business impact to product and platform teams
- Apply AI tooling to our daily work - evaluate tools and agents, identify where they add leverage, and share what works with the team
- Support the onboarding of new team members and help raise the standard for technical investigation and customer communication
Qualifications- 5+ Years: 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 how a support team works: documentation, playbooks, processes, 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 central logging platforms (Kibana / OpenSearch / Elasticsearch or similar) is a strong plus
- Comfortable searching logs, reading distributed traces, querying metrics
- Solid SQL skills - able to query relational databases to verify system state, reproduce issues, and understand data models
- Working knowledge of distributed systems concepts - async vs. synchronous communication, queues, retries, idempotency, eventual consistency
- Comfort with HTTP and API debugging - 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 with AI tooling - you already use AI in your daily work and have gone beyond typing into a chat window: built an agent, automated a workflow, written something against an API, or experimented seriously in your own time
Nice to Have- Experience reading PHP - our platform is largely PHP, so this will help you get up to speed faster
- Experience in e-commerce or digital commerce platforms (storefront, checkout, payments, catalog, order management)
- Prior incident management or major-incident response experience.
- Familiarity with PSP integrations, OMS, PIM, or search platforms
Additional InformationYour perks at a glance: Visit our benefits page.
Simply apply online via our career page - we will get back to you as soon as possible!
(Please note that benefits may vary depending on the location)
