AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Define and lead Sharecare’s transformation into the era of agentic engineering.

• Enhance and optimize the Factory spine to maximize throughput in agentic engineering.

• Advance factory platform capabilities, including merge gates, migration safety, canary deployment, and rollback functionalities.

• Oversee the application work spine that enables AI agents and humans to engage in patient care with auditability and fail-closed checks.

• Manage the warehouse, analytics platform, data pipelines, and performance metrics.

• Design, develop, test, deploy, and maintain AI and machine learning solutions.

• Build and refine machine learning models, predictive analytics solutions, recommendation systems, and intelligent automation tools.

• Develop generative AI applications utilizing LLMs, RAG, and conversational AI technologies.

• Integrate AI and machine learning models into enterprise applications, workflows, and business processes.

• Create and sustain data pipelines for model training, evaluation, deployment, and monitoring.

• Assess emerging AI technologies, frameworks, and platforms.

• Monitor model performance and implement retraining, optimization, and lifecycle management strategies.

• Ensure AI solutions comply with security, privacy, governance, and compliance standards.

• Conduct testing, validation, and performance evaluations of models and AI applications.

• Collaborate with cloud engineering and infrastructure teams to deploy and scale AI solutions effectively.

• Produce technical documentation, architecture diagrams, and operational procedures.

• Support AI governance initiatives focused on transparency, explainability, fairness, and responsible AI practices.

• Troubleshoot technical challenges associated with AI models, integrations, and production environments.

• Engage in code reviews, solution design sessions, and architectural planning.

• Provide technical leadership regarding AI best practices and implementation strategies.

• Contribute to the organization's AI roadmap and strategic innovation initiatives.

⛳️ Requirements

• A Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Mathematics, Statistics, Information Technology, or a related field is required.

• A minimum of 4 years of experience in software engineering or systems architecture is necessary.

• Proven experience in developing, deploying, and supporting machine learning models and AI-driven applications.

• Familiarity with cloud platforms such as Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP).

• Knowledge of model governance, monitoring, and lifecycle management.

• Understanding of cloud-native AI services, distributed computing, and scalable architecture principles.

• Awareness of data privacy, cybersecurity, compliance, and responsible AI practices.

• Preferred experience in developing solutions using LLMs, generative AI platforms, and natural language processing tools.

• Experience with model deployment, MLOps, DevOps, CI/CD pipelines, and containerization technologies is preferred.

• Previous experience in healthcare and/or clinical research is a plus.

• Strong analytical, problem-solving, and critical-thinking abilities.

• Capability to translate complex technical concepts into business-relevant solutions and recommendations.

• Excellent collaboration and teamwork skills.

• Ability to manage multiple priorities and projects in a dynamic environment.

• High degree of professionalism, integrity, and accountability.

🏝️ Benefits

• Comprehensive health insurance coverage.

• Flexible work schedule with remote work options.

• Opportunities for professional development and continuing education.

• Generous paid time off and holiday policies.

• Collaborative and innovative work environment.