Team Lead - Conversational Agents
TLDR
Architect enterprise AI platforms with LLMs, RAG, and Agentic AI while scaling chatbots and establishing engineering standards.
Team Lead - Conversational Agents
Experience: 10+ Years
Location: Hybrid
About the Role
We are seeking a seasoned Team Lead - Conversational Agents to lead, mentor, and grow an engineering team focused on architecting and delivering next-generation AI-powered voice, digital, and enterprise conversational platforms.
In this role, you will bridge technical leadership, enterprise architecture, and team management. Beyond driving hands-on innovations with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI, you will be responsible for scaling enterprise chatbots, setting engineering standards, and fostering the professional growth of your team.
Key Responsibilities
Technical Leadership & Enterprise Architecture
- Architect, build, and deploy robust, enterprise-grade digital and voice assistants, chatbots, and AI agent platforms at scale.
- Oversee multi-step AI workflow orchestration, tool/function calling, state management, and RAG pipelines integrated with complex enterprise backends.
- Drive quality assurance, performance optimization, model evaluation, safety guardrails, and compliance across all conversational touchpoints.
Team Leadership & Growth
- Lead a team of small-to-medium-sized AI Conversational Engineers, providing technical guidance, career development, mentorship, and continuous growth opportunities.
- Establish engineering best practices, standards, and testing methodologies.
Collaboration & Delivery Management
- Partner closely with product managers, business stakeholders, and cross-shore engineering teams to align business goals with execution strategies.
- Drive project delivery timelines, manage technical risks, remove blockers, and ensure high-quality software releases.
Required Skills & Qualifications
Leadership & Core Experience
- 10+ years of total software engineering experience.
- 2+ years of experience leading, managing, or mentoring small-to-medium engineering teams.
- Proven track record of building and successfully deploying enterprise-scale chatbots, conversational AI platforms, or digital assistant solutions.
- Advanced Python programming, code architecture, and asynchronous frameworks (e.g., FastAPI).
- Experience with RESTful APIs, webhooks, microservices architecture, and integrating with enterprise knowledge sources/databases.
- CI/CD pipelines, Git workflows, automated unit/integration testing, cloud infrastructure (AWS/GCP), and security best practices.
- Good understanding of Large Language Models (LLMs), Prompt Engineering, RAG architectures, and Agentic AI systems.
- Experience with Model Context Protocol (MCP), tool/function calling, and AI workflow orchestration engines.
- Hands-on familiarity with modern frameworks (LangChain, LangGraph) and Vector Databases (Pinecone).
Ideal Candidate Profile
- A proactive leader who leads by example, balances technical excellence with empathy, and takes personal responsibility for team success and growth.
- Passionate about converting cutting-edge GenAI research into stable, secure, high-value business applications for enterprise clients.
- Ability to articulate complex technical concepts clearly to non-technical stakeholders and executive leadership.
RingCentral is a global leader in cloud unified communications and collaboration solutions, offering an integrated platform that combines business phone, SMS, contact center, video collaboration, and messaging. Their innovative use of voice AI enhances business communications, allowing organizations to automate calls and improve interactions at every stage of the conversation journey.
- Founded
- Founded 1999
- Employees
- 500+ employees
- Industry
- computer software
- Funding stage
- Public
- Stock ticker
- Publicly traded (RNG)
- Total raised
- $1.7B raised