Additionalinformation

Additional Information

All your information will be kept confidential according to EEO guidelines.

Your 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) A Place Where You Can Be You We take it as our responsibility to create an environment where everyone feels welcome, exactly as they are. Different backgrounds and perspectives make us stronger and shape our culture in ways that matter. What we stand for internally, we stand for as a brand: acceptance, inclusion, and fairness.

Companydescription

Company Description

SCAYLE is one of the fastest-growing enterprise commerce platforms in the world, enabling brands and retailers to realize their D2C ambitions. SCAYLE stands for innovation, international collaboration, and a strong focus on data. We believe that stepping outside of our comfort zone and making bold decisions is key to growing both professionally and personally. Instead of seeing problems as obstacles, we approach them as opportunities to find better solutions. We work in an environment that encourages flexibility, creativity, and continuous development. What drives us is the shared motivation to make an impact and actively shape the future of eCommerce.

Jobdescription

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