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Ema Logo Ema · IT - Administration

Senior Support Engineer

India, Bengaluru · Job Posted February 21, 2026
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Job Description

You are a Senior Support Engineer who delivers world-class post-deployment support for product and solution deployments. You are highly customer-oriented, calm under pressure, and excellent at triaging complex issues, reproducing problems, and driving cross-functional resolution with Implementation and Engineering teams. You act as the customer’s advocate while ensuring issues are tracked, prioritized, and resolved with clarity, urgency, and high quality.

Job Responsibility

  • Own customer-facing incident management and escalations for post-deployment enterprise accounts
  • Triage incoming issues by gathering context, logs, steps-to-reproduce, and customer impact
  • Create clear, actionable bug reports and support tickets with detailed reproduction steps and diagnostics
  • Coordinate closely with Implementation and Engineering teams to drive timely issue resolution
  • Track and manage SLAs and key support metrics including FRT, TAT, AHT, and CSAT
  • Provide proactive, regular status updates to customers and internal stakeholders
  • Communicate effectively with both technical and non-technical customer teams during incidents and escalations
  • Identify recurring issues and contribute to improvements in documentation, runbooks, and support processes
  • Maintain and enhance internal knowledge bases, troubleshooting guides, and escalation playbooks
  • Validate fixes, coordinate customer confirmation, and support post-resolution follow-ups
  • Participate in escalation and on-call rotations as required

Requirements

  • 4+ years of experience in Support Engineering, Software Engineering, or Technical Customer Support
  • Hands-on experience supporting AI/LLM-based applications in production environments
  • Experience configuring, deploying, or supporting AI agents, workflows, or ML systems
  • Exposure to prompt engineering and iterative improvement of LLM outputs
  • Experience running UATs or customer-facing evaluations for AI systems
  • Proven ability to manage complex enterprise customer issues independently
  • Familiarity with support metrics such as FRT, AHT, TAT, CSAT
  • Strong production troubleshooting skills, including diagnosing AI performance and recommending improvements to accuracy and business KPIs
  • Strong understanding of LLM application architecture, including: Prompting patterns (system/instructions, few-shot, structured outputs, function/tool calling), Agentic workflows and orchestration concepts, RAG fundamentals (chunking, embeddings, retrieval, reranking, context windows), Evaluation concepts (golden datasets, offline/online evals, quality metrics, regression testing)
  • Ability to diagnose ML/LLM performance issues and recommend next-step experiments or mitigations (guardrails, routing, prompt adjustments, data fixes)
  • Proficiency with APIs and integrations: JSON, REST (and SOAP where relevant), auth basics (tokens, OAuth), and troubleshooting payload/schema issues
  • Good understanding of backend concepts that affect AI systems: latency, retries, timeouts, queues, rate limits, and distributed system failure modes
  • Ability to read logs and understand API request/response flows
  • Experience with ticketing, incident management, and customer communication tools
  • Excellent communication skills, both written and verbal
  • Ability to work effectively with technical and non-technical stakeholders
  • High ownership and accountability for customer outcomes
  • Strong analytical and problem-solving mindset, especially under production pressure
  • Curiosity and willingness to continuously learn new GenAI and automation techniques
  • Collaborative team player who works seamlessly across Support, Engineering, Product, and Customer Success
  • Deep customer empathy, always prioritizing real business impact
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