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.
