Team Lead - Conversational Agents

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.