AI Engineer- Remote

Overview

Sharecare is seeking an AI Engineer to help define and drive the transformation of Sharecare into the era of agentic engineering, owning problem domains end to end across the factory platform, the application work spine, and data and metrics.

What you'll do

• Design, develop, test, deploy, and maintain AI and machine learning solutions to support business needs.
• Build and optimize machine learning models, predictive analytics solutions, recommendation systems, and intelligent automation tools.
• Develop and implement generative AI applications utilizing large language models (LLMs), retrieval-augmented generation (RAG), and conversational AI technologies.
• Collaborate with business stakeholders to understand requirements and translate business challenges into AI-driven solutions.
• Integrate AI and machine learning models into enterprise applications, workflows, and business processes.
• Develop and maintain data pipelines that support model training, evaluation, deployment, and ongoing monitoring.
• Evaluate emerging AI technologies, frameworks, and platforms to identify opportunities for innovation and business improvement.
• Monitor model performance and implement processes for model retraining, optimization, and lifecycle management.
• Ensure AI solutions meet security, privacy, compliance, and governance standards.
• Conduct testing, validation, and performance assessments of machine learning models and AI applications.
• Collaborate with cloud engineering and infrastructure teams to deploy and scale AI solutions in cloud environments.
• Develop technical documentation, architecture diagrams, and operational procedures for AI systems.
• Support AI governance initiatives, including model transparency, explainability, fairness, and responsible AI practices.
• Troubleshoot and resolve technical issues related to AI models, integrations, and production environments.
• Participate in code reviews, solution design sessions, and architectural planning activities.
• Provide technical leadership and guidance on AI best practices and implementation strategies.
• Stay current with advancements in artificial intelligence, machine learning, data science, and related technologies.
• Support strategic innovation initiatives and contribute to the organization's AI roadmap.
• Develop and improve the existing factory platform: merge gates, migration safety, and canary and rollback for systems where a bad deploy can touch patient care.
• Increase throughput by 50% while maintaining a lean team.
• Own the application work spine: guardrails with auditability and fail-closed checks so AI agents and humans can safely act on patient care.
• Own the data and metrics layer: warehouse, analytics platform, and the pipelines that show what happened.

What you'll need

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Mathematics, Statistics, Information Technology, or a related field.
• Minimum of at least 4 years of experience in software engineering or systems architecture.
• Experience developing, deploying, and supporting machine learning models and AI-driven applications.
• Demonstrated ability to ship daily at high volume with a fleet of AI agents.
• Experience owning architecture across multiple companies or many codebases (staff-plus IC, chief-architect, or platform-consulting background).
• 6+ years and multiple systems owned end to end.
• Strong analytical, problem-solving, and critical-thinking skills.
• Ability to translate complex technical concepts into business-focused solutions and recommendations.
• Strong collaboration and teamwork skills with the ability to work effectively across technical and business functions.
• Ability to manage multiple priorities and projects in a fast-paced environment.
• Knowledge of data privacy, cybersecurity, compliance, and responsible AI practices.
• High level of professionalism, integrity, and accountability.

Nice to have

• Experience developing solutions using large language models (LLMs), generative AI platforms, and natural language processing tools.
• Experience with cloud platforms such as Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP).
• Experience with model deployment, MLOps, DevOps, CI/CD pipelines, and containerization technologies.
• Familiarity with model governance, monitoring, and lifecycle management.
• Knowledge of cloud-native AI services, distributed computing, and scalable architecture principles.
• Prior experience in healthcare and/or clinical research, on health data products including electronic health records, claims, wearables, and/or remote patient monitoring technologies.
• Communicates proactively in writing.

Details

• Work mode: Remote.
• Sharecare and its subsidiaries are Equal Opportunity Employers and E-Verify users.