AI Linguist

Key Responsibilities

• Elicit business goals, user journeys, intents/entities, FAQs, and deflection targets with stakeholders (CX, Operations, Legal).
• Translate requirements into measurable NLU/LLM specs and acceptance criteria.

• Design intents, entities, dialogue flows, handoffs, error recovery, and tone of voice.
• Author prompts, system instructions, tool-use policies, and safety guardrails.
• Create high‑quality utterance datasets, synonyms, lexical/regex patterns, and grammars.

• Build and fine‑tune NLU/LLM components (classification, NER, summarization, RAG over knowledge bases).
• Configure ASR/TTS for omnichannel (voice/chat/messaging).
• Implement data quality checks, PII redaction/anonymization, and prompt/content moderation.

• Define and execute unit, integration, regression, A/B, and user acceptance tests.
• Evaluate with task metrics (containment, deflection, FCR, AHT impact, CSAT), and model metrics (precision/recall, F1, latency, hallucination rate).

• Support CI/CD pipelines, release notes, and rollback plans.
• Monitor production with analytics dashboards, conversation reviews, error triage, and incident response.
• Drive continuous improvement via data‑driven tuning and content updates.

• Ensure GDPR/LOPDGDD compliance, consent, data minimization, and retention policies.
• Apply Responsible AI practices (bias/fairness checks, safety red‑teaming, documentation).

• Partner with Contact Center Ops, QA, Knowledge Management, CRM teams, and vendor partners.
• Provide enablement materials and training for agents and supervisors.

Skills Knowledge and Expertise

• Participation in bot projects (voicebots, chatbots, virtual assistants, etc.) involving conversational flows, open questions, automation, NLU technologies (voice recognition, classification, voice synthesis), and generative AI.
• Experience in customer relations, requirements gathering, design, validation, etc.
• Experience in recognition models (SST, TTS, NLU) as well as in their training or continuous improvement: Microsoft STT, MS LUIS/CLU, Google, Amazon, Nuance Recognizer.
• Experience in improving UX at the design, development, analysis, and continuous improvement levels of NLP associated with bots.
• Experience in designing, writing, and improving AI prompting under different LLM models.
• Ability to analyze and participate in consulting projects where customer automation bot services have been analyzed, evaluating KPIs, and a proposal for improving their systems and services has been developed.

• Development of bots or agents using generative AI technologies such as AI Agentics architecture, Google Conversational Agent with Playbooks, Google AI Studio, Gemini, OpenAI, Amazon Bedrock, Microsoft Azure AI, other AI architectures, or LLMs...
• Bot development using conversation technologies such as DialogFlow, Genesys Dialog Engine, Nuance Mix, Microsoft Bot Framework, and VXML.
• Knowledge and experience in programming and scripting (Javascript/Node, Python, Java bash, etc.).
• Proficiency and experience with project development tools and methodologies. IDEs, code repositories (mainly git), Agile

Benefits