Conversational AI & Language Engineering Lead

Conversational AI & Language Engineering Lead

Responsible for defining and leading the engineering approach for complex features to deliver significant business outcomes. This senior leadership position sets the technical vision, manages teams, and ensures the long‑term health and performance of the machine learning capabilities powering Bank of America’s employee‑facing Virtual Assistant.

• Own the end‑to‑end technical strategy for language engineering, NLU, and conversational AI across web, mobile, and voice channels.
• Define and evolve the intent portfolio and domain coverage, ensuring alignment between conversation design, business needs, and ML capabilities.
• Establish standards and best practices for model quality, evaluation, telemetry, and lifecycle management.
• Provide senior‑level technical oversight for model design, training approaches, performance tradeoffs, and production readiness.
• Serve as the accountable owner for model governance, including current and future registered models.
• Help transition a mature deterministic solution with over 650 capabilities to leverage generative and agentic AI.
• Define the conversational AI roadmap, integrating traditional NLU techniques with LLM and GenAI capabilities where appropriate.
• Partner with product owners, UX researchers, data scientists, and engineering leaders to shape the “brain” of the virtual assistant.
• Translate complex technical topics into clear, executive‑level communication for stakeholders and leadership.
• Identify systemic gaps or under‑performing areas through analytics and conversation monitoring and drive multi‑quarter improvement plans.

• Proven experience leading teams delivering conversational AI, NLP, or language‑driven ML solutions.
• Strong background in natural language processing, intent classification, and speech recognition, with the ability to guide others rather than execute all work personally.
• 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 sufficient to provide technical leadership and oversight.
• Experience with Agile and Dev Ops operating models.
• Strong analytical thinking, decision‑making, and executive communication skills.

Shift: 1st shift (United States of America). Hours per week: 40.

Pay range: $122,000 – $200,000 annualized salary, offers to be determined based on experience, education and skill set. Discretionary incentive eligibility: employees may qualify for an annual discretionary award.