Conversational Data Engineer

ApTask is a global provider of workforce solutions and talent acquisition services. The Conversational Data Engineer will create customer-specific synthetic data and own RAG and knowledge pipelines for conversational AI, voice, and chat deployments. The role also involves generating and validating synthetic content, maintaining reusable ingestion and quality processes, and partnering with platform and DevOps teams to automate isolated customer environments.

Responsibilities:

• Analyze each customer’s domain: intents, entities, knowledge topics, document types, languages, tone, and edge cases
• Generate synthetic conversation transcripts for voice and chat, plus CCAI training/evaluation dialogues
• Generate supporting content: customer/agent profiles, knowledge-base articles, FAQs, and structured entity values
• Schedule and document index refresh processes when customer knowledge changes
• Use appropriate techniques while documenting parameters and limitations
• Validate realism, coverage, diversity, and absence of residual real-world PII in synthetic data and source corpora
• Maintain reusable generators, ingestion jobs, and quality checklists that can be parameterized per customer
• Partner with the Conversational Platform Specialist so loaded data and indexes actually drive the deployed experience
• Partner with DevOps so pipeline jobs, stores, and secrets are automated and isolated per customer

Requirements:

• 4+ years in data engineering, conversation design operations, applied NLP data work, or knowledge-pipeline engineering
• Working knowledge of how conversational platforms consume training, FAQ, transcript, and retrieval-grounded knowledge data
• Strong judgment on synthetic-data quality, retrieval quality, and privacy safety
• LLM-assisted synthetic data generation in a production or implementation setting
• Familiarity with BigQuery, S3, and document stores used as knowledge sources
• Multilingual data generation or evaluation experience