Lead Software Engineer (Conversational Voice Design)
Role details
Job location
Tech stack
Job description
We are looking for a Lead Software Engineer to drive the architecture, design, and development of AI-powered conversational and automation solutions within a cloud-native environment. The role will focus on building scalable bot platforms and leveraging modern AI/ML capabilities using Google Cloud technologies and enterprise-approved GenAI tools to support business transformation initiatives.
Responsibilities
Lead technical design and architecture for conversational AI and bot solutions.
Drive hands-on development and guide the engineering team through implementation and delivery.
Develop and optimize AI/ML and LLM-based solutions using Google Cloud technologies.
Ensure adoption of enterprise-approved AI tools to improve engineering productivity and delivery quality.
Collaborate with cross-functional teams to define scalable and maintainable technical solutions.
Skills
Must have
Software Architecture
Google Cloud Platform (GCP)
Google DialogFlow
Vertex AI
Agent Development Kit (ADK)
Large Language Models (LLMs)
Python / Java / Go
Requirements
Do you have experience in Tooling?, Do you have a Master's degree?, Bachelor's or Master's degree in Computer Science or related field. Minimum 5 years of experience in software architecture or AI/ML engineering, including at least 2 years of hands-on experience with Google Cloud Platform. Strong experience designing and developing conversational AI solutions using Google DialogFlow, Vertex AI, ADK, and LLM technologies. Proficiency in Python, Java, or Go is required. Candidates are expected to demonstrate day-to-day usage of enterprise-approved AI tools (e.g., GitHub Copilot, Microsoft 365 Copilot, and approved GenAI platforms) to improve coding efficiency, documentation quality, analysis, and decision-making while maintaining continuous learning of emerging AI capabilities.
Google Cloud certification. Experience with Generative AI, prompt engineering, and advanced LLM use cases. Healthcare industry experience or exposure to healthcare systems is preferred but not required.
Nice to have
Experience leading engineering teams and driving AI adoption at scale is a plus.
Exceptional communication skills.
Ability to deliver exceptional customer service with a positive attitude.