About the Role / About the Job
We are looking for an Engineer - OpenAI & Chatbot Support to operate, monitor, troubleshoot, and continuously improve enterprise generative-AI and chatbot services. The role focuses on service availability, response-quality investigation, knowledge-base operations, prompt and configuration support, integration troubleshooting, responsible-AI controls, and SLA-driven production support.
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Responsibilities
- Monitor chatbot and generative-AI services for availability, latency, errors, usage, and operational health.
- Triage and resolve incidents involving conversation flows, model endpoints, prompts, knowledge retrieval, APIs, authentication, and dependent services.
- Investigate inaccurate, incomplete, unsafe, or irrelevant chatbot responses and document evidence-based corrective actions.
- Maintain approved prompts, system instructions, chatbot topics, knowledge sources, configuration records, and version history.
- Support retrieval-augmented generation workflows, content ingestion, indexing, access controls, and knowledge refresh activities.
- Validate releases and configuration changes across development, testing, and production environments.
- Analyse logs, traces, user feedback, and usage metrics to identify recurring issues and improvement opportunities.
- Apply approved responsible-AI, privacy, security, content-safety, and human-escalation controls.
- Coordinate with application, Data & AI, security, cloud, and business teams for L2/L3 escalation and problem resolution.
- Maintain operational SOPs, known-error records, support knowledge articles, test evidence, and service reports.
- Understand and usage on prompt engineering.
Technical Skills
- Azure OpenAI or comparable enterprise LLM services; deployment, configuration, endpoint, and operational support awareness.
- Microsoft Copilot Studio, Azure Bot Service, Bot Framework, or comparable chatbot platforms.
- RAG concepts, document ingestion, chunking awareness, vector and semantic search, grounding, and knowledge-base maintenance.
- Prompt configuration, conversation flows, fallback handling, escalation paths, response-quality testing, and version control.
- REST APIs, JSON, authentication, connectors, webhooks, and troubleshooting of dependent application integrations.
- Logging, tracing, analytics, content filtering, privacy controls, access controls, and responsible-AI operational practices.
- Incident, problem, change, release, SLA, runbook, and knowledge-management practices.
Good To Have
- Experience with Azure AI Search and enterprise knowledge bases.
- Exposure to Semantic Kernel or agent orchestration frameworks.
- Experience with LLM observability, evaluation, or prompt-testing tools.
- Relevant Microsoft Azure, AI, or ITIL certifications.
- Exposure to front-end stacks like next.js, react.js.
- Experience in Python.
Qualifications
- Bachelor's or Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field.
Soft Skills
- Strong analytical, problem-solving, and troubleshooting skills.
- Excellent communication and documentation abilities.
- Ability to work independently and collaborate effectively across technical and service-management teams.
- Customer-focused mindset with disciplined ownership of incidents, requests, and operational commitments.
