Own the end-to-end technical strategy for language engineering, NLU, and conversational AI.
Define and evolve the intent portfolio and domain coverage.
Establish standards and best practices for model quality and lifecycle management.
Serve as the accountable owner for model governance.
Lead and develop a medium-sized team of language engineers and ML practitioners.
Define the conversational AI roadmap and partner with product owners and researchers.

Requirements

Proven experience leading teams delivering conversational AI, NLP, or language-driven ML solutions.
Strong background in natural language processing, intent classification, and speech recognition.
Experience shaping and executing technical strategy across multiple domains and channels.
Familiarity with LLMs and GenAI, including their application, limitations, and governance considerations in enterprise environments.
Working knowledge of Python, ML workflows, and evaluation techniques.
Experience with Agile and DevOps operating models.
Strong analytical thinking, decision-making, and executive communication skills.

Benefits

Industry-leading benefits
Access to paid time off
Resources and support to employees for genuine impact and contributions

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

natural language processingintent classificationspeech recognitionPythonmachine learning workflowsevaluation techniquesconversational AIlanguage-driven MLlarge language modelsgenerative AI

Soft Skills

analytical thinkingdecision-makingexecutive communicationteam leadership