Senior GenAI & Machine Learning

About the role

As an AI Architect, you will make an impact by designing and delivering scalable, AI-driven platforms that leverage machine learning, large language models (LLMs), and generative AI to transform healthcare payer operations. You will be a valued member of the architecture and engineering team, working collaboratively with product owners, data teams, and payer business stakeholders to drive innovation while ensuring compliance with healthcare regulations and data privacy standards.

In this role, you will:

• Design and implement scalable AI architectures leveraging machine learning, LLMs, and generative AI to modernize payer workflows and improve operational efficiency
• Develop end-to-end solution blueprints covering data ingestion, feature engineering, model training, evaluation, and deployment aligned with enterprise standards
• Collaborate with business stakeholders to translate payer domain needs (claims, benefits, utilization management) into AI-driven solutions
• Build reusable AI components for use cases such as prior authorization, claims triage, fraud detection, and member engagement
• Establish responsible AI frameworks including governance, fairness, explainability, and monitoring to ensure compliant and ethical AI solutions

Work model

We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a hybrid position in Hardfort, CT. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.

The working arrangements for this role are accurate as of the date of posting. This may change based on the project you’re engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.

What you need to have to be considered

• Strong expertise in machine learning (supervised and unsupervised), including feature engineering, model validation, and production deployment
• Hands-on experience building and integrating large language model (LLM) solutions, including retrieval-augmented generation (RAG), conversational AI, and document intelligence
• Proven experience designing and deploying generative AI solutions such as summarization, recommendation systems, and intelligent assistants
• Deep understanding of healthcare payer operations (claims adjudication, benefits, eligibility, prior authorization, provider networks)
• Knowledge of healthcare standards, regulations, and compliance requirements (e.g., HIPAA, coding systems)
• Strong programming skills and experience with AI/ML frameworks and cloud-based AI platforms, including MLOps practices
• Experience designing scalable, enterprise-grade AI solutions with observability, monitoring, and performance optimization

These will help you stand out

• Experience optimizing LLM-based solutions including prompt engineering, retrieval design, and context management tailored to domain-specific use cases
• Familiarity with AI governance frameworks, including model explainability, bias mitigation, and lifecycle monitoring
• Experience defining data models, pipelines, and quality frameworks for large-scale AI solutions
• Ability to lead architecture discussions, perform design/code reviews, and define long-term technical strategy
• Strong stakeholder communication skills with the ability to translate complex AI concepts to both technical and non-technical audiences

We’re excited to meet people who share our passion for innovation and can make an impact in a variety of ways. Don’t hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting ideas to this role.