Staff Conversational AI Engineer

Collective Health•Lehi, UT

1d•$155,500 - $243,500•Hybrid

About The Position

At Collective Health, we’re transforming how employers and their people engage with their health benefits by seamlessly integrating cutting-edge technology, compassionate service, and world-class user experience design. As the Staff Conversational AI Engineer, you will be at the forefront of architecting, designing and implementing intelligent and natural conversational solutions. You will work hands-on with Google's CCAI suite, including Dialogflow CX, Agent Assist, Vertex AI and CCAI Insights, to create seamless and personalized user journeys. Your work will directly contribute to improving member satisfaction, streamlining internal workflows, and solidifying Collective Health's position as an innovator in the healthcare industry.

Requirements

Proven, hands-on experience in designing, building, and launching production-level conversational AI experiences is essential for success in this role.
10+ years of overall development experience in CCaaS platforms with recent experience in developing conversational self service agents.
In-depth knowledge and practical experience with the Google Cloud Contact Center AI (CCAI) platform, including Dialogflow CX, Agent Assist, and CCAI Insights.
Strong understanding of natural language understanding (NLU), natural language generation (NLG), multi-language support and the principles of conversational design.
Experience in training chatbots by analyzing historical chat conversations or large amounts of user generated content and process data
Practical knowledge of formal syntax, formal semantics, corpus analysis, dialogue management
Experienced in prompt engineering, building, enhancing and maintaining custom RAG pipelines.
Proficiency in javascript and in one or more languages such as Python or Java.
Experience with API integrations and connecting conversational interfaces with backend systems and data sources.
Demonstrated ability to lead and mentor engineering teams, with a passion for sharing knowledge and fostering technical growth.
Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and stakeholders.
A strategic mindset with the ability to translate business needs into technical solutions and a long-term vision for conversational AI.
Understanding of training classical Machine learning algorithms along with an understanding of choosing the right evaluation metric
A bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.

Nice To Haves

Knowledge of training and tuning topic modelling algorithms like LDA and NMF is a huge plus.
Experience Optimizing LLM engines.
Experience building AI applications with Claude, OpenAI or LLaMa models.

Responsibilities

Lead the architecture, design, development, and deployment of sophisticated conversational AI applications on the Google CCAI platform to serve a variety of consumer and internal use cases.
Architect and build robust, scalable, and maintainable conversational flows and virtual agents using Google Dialogflow CX and DialogFlow APIs.
Define processes and optimize them continuously for seamless migration of agents across various environments.
Integrate and optimize Google Agent Assist to empower our member-facing teams with real-time guidance and support.
Leverage CCAI Insights to analyze conversation data, identify trends, and continuously improve the performance and effectiveness of our AI-driven interactions.
Provide technical leadership and mentorship to a team of engineers, fostering a culture of innovation and excellence in the AI space.
Collaborate closely with product managers, designers, and other engineering teams to define the product vision, roadmap, and user experience for conversational AI initiatives.
Manage stakeholder expectations and communicate technical concepts and project progress to both technical and non-technical audiences.
Stay at the forefront of advancements in conversational AI, natural language processing (NLP), and large language models (LLMs), and champion the adoption of new technologies and best practices.
Be a part of incident management/247 support for CCaaS on rotation basis.