Conversational AI & Language Engineering Lead

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At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!

Conversational AI & Language Engineering Lead

This job is responsible for defining and leading the engineering approach for complex features to deliver significant business outcomes. Key responsibilities of the job include delivering complex features and technology, enabling development efficiencies, providing technical thought leadership based on conducting multiple software implementations, and applying both depth and breadth in a number of technical competencies. Additionally, this job is accountable for end-to-end solution design and delivery.

The Conversational AI & Language Engineering role, is a senior leadership position, responsible for setting the technical vision, managing teams, and ensuring the long-term health and performance of the machine learning capabilities powering Bank of America’s employee facing Virtual Assistant.

This role is leadership first: accountable for strategy, governance, prioritization, and outcomes across natural language understanding (NLU), speech recognition, and LLM based capabilities.

Additionally, this job is accountable for end-to-end solution design and delivery.

Key Responsibilities

Technology Leadership & Ownership

• 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 (e.g., technology, human resources), 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.

Strategy, Roadmap & Stakeholder Partnership

• 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 underperforming areas through analytics and conversation monitoring and drive multi‑quarter improvement plans.

Required Skills & Experience

• 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 DevOps operating models.

• Strong analytical thinking, decision‑making, and executive communication skills.

Shift:

Hours Per Week: