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AI Engineer

• Enablement & coaching — work directly with engineers through 1:1s, pair programming, workshops, office hours, and cohorts to raise their effectiveness with AI-assisted development: prompting, workflow design, and model/tool selection. Identify under-adoption and lift teams up to the standard.
• Best-practice propagation — capture what works (and what fails) in one team and systematically transfer it: living best-practice guides, prompt libraries, troubleshooting playbooks, and an internal AI knowledge base and skills registry.
• Scale through champions — stand up and support a network of embedded AI champions so enablement scales past a single person.
• Unblocking & feedback loop — be the go-to when engineers get stuck with AI tooling. Proactively tour teams to surface blockers early, aggregate them into patterns, and escalate systemic issues to leadership.
• Internal integrations & tooling — build internal AI integrations and reusable tooling hands-on (Node.js/TypeScript, MCP) — from prototype to production independently, including auth, access control, security review, and CI/CD.
• Evaluation & scouting — run structured evaluations of AI tools, models, and internal integrations; monitor the fast-moving landscape (Claude Code, Cursor, Copilot/Codex, new model releases) and deliver curated, actionable recommendations.
• Measurement & impact — define and track adoption and productivity metrics by team, tool, and individual. Build dashboards on real usage and output — adoption/active-usage rate, assistant acceptance rate, PR throughput and cycle time — with a quality guardrail (change failure rate) so speed never comes at the cost of quality. Reference frameworks: DX Core 4, DORA.
• Cross-functional partnering — partner with security/compliance on safe-by-design guardrails, and with GTM to translate field needs into internal enablement and feed adoption patterns back.

Senior AI Enablement Engineer

DevOps Engineer

• Own one of our core platform areas end-to-end: observability (VictoriaMetrics, Grafana, Graylog / VictoriaLogs, fluent bit, exporters, alerting) or CI/CD (Jenkins scripted pipelines, Harbor, Nexus, build agents) — you drive its architecture, reliability, and roadmap.
• Drive technical initiatives end-to-end: gather requirements, write the design doc, decompose into tasks, implement, deliver to production, and own the operational health afterwards.
• Drive clarity in ambiguous situations by defining requirements, assumptions, and next steps.
• Design for reliability and scale: evolve the architecture of our platforms — topology, integration points, scaling approach, and reliability model.
• Support developers: deploy and monitor applications on both on-premise servers and Kubernetes (Helm), troubleshoot builds and deploys, help teams with metrics, alerts, and logs; participate in chat duty in developer support channels.
• Automate away toil: repetitive operations, provisioning, and maintenance should be codified, not performed by hand.
• Investigate production incidents as the senior escalation point for your area: drive resolution, lead post-mortems, implement systemic fixes. Participate in on-call rotations and raise the bar for how on-call works.
• Mentor less experienced engineers through design discussions, reviews, and pairing; catch debt-inducing shortcuts at the review stage.
• Use AI in all aspects of day-to-day work: researching, troubleshooting, developing.

Senior DevOps Engineer

• Own one of our core platform areas end-to-end: observability or CI/CD — you drive its architecture, reliability, and roadmap.
• Drive technical initiatives end-to-end: gather requirements, write the design doc, decompose into tasks, implement, deliver to production, and own the operational health afterwards.
• Drive clarity in ambiguous situations by defining requirements, assumptions, and next steps.
• Design for reliability and scale: evolve the architecture of our platforms — topology, integration points, scaling approach, and reliability model.
• Support developers: deploy and monitor applications on both on-premise servers and Kubernetes (Helm), troubleshoot builds and deploys, help teams with metrics, alerts, and logs; participate in chat duty in developer support channels.
• Automate away toil: repetitive operations, provisioning, and maintenance should be codified, not performed by hand.
• Investigate production incidents as the senior escalation point for your area: drive resolution, lead post-mortems, implement systemic fixes. Participate in on-call rotations and raise the bar for how on-call works.
• Mentor less experienced engineers through design discussions, reviews, and pairing; catch debt-inducing shortcuts at the review stage.
• Use AI in all aspects of day-to-day work: researching, troubleshooting, developing.