Senior Technical Support Specialist

• Ema is building the world’s first Universal AI Employee — a production-grade agentic AI platform that automates real enterprise workflows across HR, IT, Finance, and Operations
• Ema’s customers do not run demos. They replace mission-critical, manual business processes with agentic AI systems that operate across multiple SaaS tools, APIs, and human-in-the-loop workflows
• In this world, support is not reactive. Support is production reliability, trust preservation, and system learning. At Ema, Senior Technical Support Specialists are operators of live AI systems, not ticket handlers
• The Senior Support Engineer owns the health, reliability, and trustworthiness of Ema’s deployed agentic AI systems in production. This role sits at the intersection of:
• AI behavior
• Workflow orchestration
• Enterprise integrations
• Customer trust
• Engineering feedback loops
• This is:
  Not L1 / call-center support, Not a “just
• This is: A senior technical escalation role, A production debugging and RCA role, A partner to Engineering, Product, and Implementation, A role with real authority during incidents
• You are the last line of defense between a production issue and customer trust erosion
• You prevent small failures from turning into account-level crises
• You ensure learnings from incidents improve the product and delivery systemically
• Customers trust Ema because issues are handled competently and transparently
• AI failures are explained, mitigated, and prevented — not hand-waved
• Production stability improves over time, not degrades
• You gain rare experience operating agentic AI systems in production
• You build deep expertise across AI, integrations, and workflows
• You can grow into Reliability Engineering, Implementation Leadership, or Product-facing roles
• Diagnosing failures in multi-agent AI workflows
• Deeply understanding Ema’s platform and providing workarounds/alternate approaches to customers facing issues
• Debugging issues spanning:
• AI behavior (false positives / negatives)
• Workflow logic
• Integrations (HRIS, ITSM, IAM, Finance)
• Data quality
• Platform configuration
• Handling Sev-1 / Sev-2 customer specific incidents calmly under customer pressure
• Help Engineering & Product teams Prevent repeated incidents through disciplined RCA
• Converting noisy customer complaints into high-signal engineering feedback
• Own customer-reported issues from intake to resolution adhering strictly to SLAs
• Take responsibility for diagnosis, coordination, and closure;
  Importantly, provide workarounds to customers to unblock them while engineering fix is made
• Ensure no issue is “lost” between teams
• Act as technical owner even when multiple teams are involved
• Debug agentic workflows end-to-end
• Trace failures across agents, tools, integrations, and humans-in-the-loop
• Identify whether issues are caused by:
• Model behavior
• Prompt / policy logic
• Integration constraints
• Customer configuration
• Provide clear, actionable root cause summaries
• Resolve Sev 1 / Sev 2 Client issues;
  Escalate to the right team to help solve and close the issue. Keep customer communication calm, factual, and confidence-building
• Communicate during incidents without speculation or panic
• Explain AI failures in a way customers can understand
• Set realistic recovery timelines
• Rebuild trust post-incident through transparency and follow-through
• Write high-signal bug reports and incident summaries
• Advocate for fixes based on customer impact, not noise
• Help Product understand real production behavior
• Ensure support insights influence roadmap and quality improvement
• Improve runbooks, playbooks, and diagnostics
• Improve on-call hygiene and escalation clarity
• Mentor junior support engineers
• Raise the overall support bar at Ema

Excellent debugging instincts

Comfortable operating in ambiguous systems

Able to isolate root cause across layers

Calm during incidents

Issues do not bounce — they get owned

Bias toward permanent fixes

Communicates clearly with both engineers and customers

Knows when to upscale and when not toCan say “we don’t know yet” credibly

Respects both customer urgency and engineering quality

Low ego, high accountability

Truth-seeking over blame

Experience supporting enterprise SaaS platforms in productionAPIs and integrations

Logs, traces, and diagnostics6–9+ years in senior technical support, reliability, or production engineering roles

Distributed systems

Customer-facing experience with senior stakeholders

Experience handling escalations and incidents

Strong understanding of:

Familiarity with AWS / GCP / Azure

Experience with workflow orchestration or agentic systems

Support or reliability roles in AI / automation platforms

Background in high-availability, 24×7 systems