AI Engineer

Job not on LinkedIn

🔥 0 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Sharecare

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2010

🏥 Healthcare

💼 Consulting

📣 Marketing

💰 $425M Post-IPO Equity on 2021-07

Healthcare • Consulting • Marketing

Sharecare is a comprehensive digital health platform designed to improve overall well-being. It provides tools and resources to help individuals manage various aspects of their health, such as physical, mental, and financial wellness. Sharecare offers personalized health navigation through its digital window, helping members track healthy habits, receive research-backed health tips, and access digital therapeutics across various conditions, including asthma and women's health. The platform integrates AI capabilities to empower users to manage their health data effectively. Partnering with CareLinx, Sharecare extends caregiving into homes, leveraging technology for data analytics and real-time coordination with clinical teams. Additionally, Sharecare collaborates with various organizations to enhance community health and well-being through innovative initiatives like the Community Well-Being Index. Its mission is to make healthcare resources more accessible and improve health outcomes while reducing care costs.

📋 Description

• Define and drive Sharecare's transformation into the era of agentic engineering • Develop and improve the Factory spine to maximize agentic engineering throughput • Evolve factory platform capabilities including merge gates, migration safety, canary deployment, and rollback • Own the application work spine enabling AI agents and humans to act on patient care with auditability and fail-closed checks • Own the warehouse, analytics platform, data pipelines, and metrics • Design, develop, test, deploy, and maintain AI and machine learning solutions • Build and optimize machine learning models, predictive analytics solutions, recommendation systems, and intelligent automation tools • Develop generative AI applications using LLMs, RAG, and conversational AI technologies • Integrate AI and machine learning models into enterprise applications, workflows, and business processes • Develop and maintain data pipelines for model training, evaluation, deployment, and monitoring • Evaluate emerging AI technologies, frameworks, and platforms • Monitor model performance and implement retraining, optimization, and lifecycle management • Ensure AI solutions meet security, privacy, compliance, and governance standards • Conduct testing, validation, and performance assessments of models and AI applications • Collaborate with cloud engineering and infrastructure teams to deploy and scale AI solutions • Develop technical documentation, architecture diagrams, and operational procedures • Support AI governance initiatives involving transparency, explainability, fairness, and responsible AI • Troubleshoot technical issues related to AI models, integrations, and production environments • Participate in code reviews, solution design sessions, and architectural planning • Provide technical leadership on AI best practices and implementation strategies • Contribute to the organization's AI roadmap and strategic innovation initiatives

🎯 Requirements

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Mathematics, Statistics, Information Technology, or a related field required • 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 • Experience with cloud platforms such as Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP) • Familiarity with model governance, monitoring, and lifecycle management • Knowledge of cloud-native AI services, distributed computing, and scalable architecture principles • Knowledge of data privacy, cybersecurity, compliance, and responsible AI practices • Experience developing solutions using LLMs, generative AI platforms, and natural language processing tools preferred • Experience with model deployment, MLOps, DevOps, CI/CD pipelines, and containerization technologies preferred • Prior healthcare and/or clinical research experience is a plus • 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 • Ability to manage multiple priorities and projects in a fast-paced environment • High level of professionalism, integrity, and accountability