Lead Conversational AI Engineer

Lehi, UT | Plano, TX

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Collective Health

Collective Health offers the first integrated solution that empowers employers to administer plans, manage costs, and take care of their people—all in one place.

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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 Conversational AI Lead Engineer, you will be at the forefront of 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.

What you'll do:

  • Lead the 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.
  • 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.

To be successful in this role, you'll need:

  • Proven, hands-on experience in designing, building, and launching production-level conversational AI experiences is essential for success in this role.
  • 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.
  • Knowledge of training and tuning topic modelling algorithms like LDA and NMF is a huge plus.
  • 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 Have:

  • Experience Optimizing LLM engines.
  • Experience building AI applications with Claude, OpenAI or LLaMa models.

Pay Transparency Statement 

This is a hybrid position based out of one of our offices: Plano, TX, or Lehi, UT. Hybrid employees are expected to be in the office two days per week.#LI-hybrid 

The actual pay rate offered within the range will depend on factors including geographic location, qualifications, experience, and internal equity. In addition to the salary, you will be eligible for stock options and benefits like health insurance, 401k, and paid time off. Learn more about our benefits at https://jobs.collectivehealth.com/benefits/.

Lehi, UT Pay Range$134,500—$168,000 USDPlano, TX Pay Range$147,800—$185,500 USD

Why Join Us?

  • Mission-driven culture that values innovation, collaboration, and a commitment to excellence in healthcare
  • Impactful projects that shape the future of our organization
  • Opportunities for professional development through internal mobility opportunities, mentorship programs, and courses tailored to your interests
  • Flexible work arrangements and a supportive work-life balance

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Collective Health is committed to providing support to candidates who require reasonable accommodation during the interview process. If you need assistance, please contact recruiting-accommodations@collectivehealth.com.

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For more information about why we need your data and how we use it, please see our privacy policy: https://collectivehealth.com/privacy-policy/.

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Tags: APIs Chatbots Claude Computer Science Conversational AI CX Engineering GCP Google Cloud Java JavaScript LLaMA LLMs Machine Learning NLG NLP NLU OpenAI Pipelines Privacy Prompt engineering Python RAG Vertex AI

Perks/benefits: Career development Equity / stock options Flex vacation Health care Insurance Transparency

Region: North America
Country: United States

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