Principal AI Engineer

Medical Guardian is a trusted leader in personal safety solutions to deliver independence for aging adults. Serving over 625,000 members, we provide innovative technology and compassionate support to help individuals live confidently and securely.

Medical Guardian is seeking a Principal AI Engineer to lead a growing team of AI engineers and data scientists in delivering scalable, production-grade AI and ML solutions. This senior technical leadership role will focus on architecting and deploying AI-driven applications, intelligent automation systems, and machine learning pipelines that drive measurable impact across our customer, product, and operational domains. 

The ideal candidate combines deep technical expertise in AI engineering with practical leadership experience, enabling cross-functional collaboration and delivering business-aligned outcomes in a regulated environment. 

Key Responsibilities 

Team & Technical Leadership: 

• Lead and mentor a team of AI engineers and data scientists to deliver high-impact, high-reliability AI solutions.
• Oversee the full AI/ML development lifecycle—from data ingestion and modeling to deployment, monitoring, and iterative improvement.
• Act as the primary technical architect for internal LLM tools (e.g., copilots, auto-reporting bots), agent workflows, and production ML models.
• Foster a culture of experimentation with emerging AI development environments like Cursor, Replit, and AI-native IDEs.

AI Solution Engineering: 

• Design and build custom AI applications using LLMs (OpenAI, Claude, Gemini) and frameworks like LangChain, Haystack, and HuggingFace.
• Integrate conversational AI, document intelligence, and predictive analytics into business systems, including Salesforce, Five9, and internal tools.
• Lead the design, development, and deployment of AI agents, machine learning models, and intelligent automation systems across member experience, internal operations, and product workflows.

Data Collaboration & Infrastructure: 

• Collaborate with data engineers and analysts to ensure AI systems are built on trustworthy, well-governed, and scalable data infrastructure.
• Work closely with the Director to align AI strategy with business KPIs and enterprise-wide digital transformation efforts.
• Contribute to the development of automation pipelines and MLOps infrastructure (e.g., MLflow, Vertex AI) for repeatable, production-ready deployments

Governance & Compliance: 

• Ensure all AI systems adhere to data governance policies and regulations (HIPAA, CCPA), with privacy-by-design principles embedded.
• Support internal reviews and documentation for AI ethics, explainability, and model risk management as part of enterprise compliance

Qualifications 

Education and Experience:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, AI/ML, or related fields.
• 8+ years of experience in AI/ML, data science, or applied machine learning, with 2+ years of hands-on experience with modern AI technologies, including LLMs, NLP, and deep learning frameworks.
• Demonstrated success deploying ML models or LLM-powered applications into production at scale.

Technical Expertise:

• Strong programming skills in Python and experience with AI/ML libraries (Scikit-learn, PyTorch, TensorFlow, HuggingFace).
• Experience with cloud platforms (Azure preferred; AWS or GCP acceptable).
• Expertise in designing and optimizing AI workflows using LangChain, Haystack, or similar orchestration frameworks.
• Familiarity with dbt, SQL, Power BI, and enterprise data integration tools.
• Familiarity with Replit, Cursor, Jupyter, and other AI-native dev environments.

Leadership and Communication: 

• Proven ability to lead multidisciplinary teams, mentor junior engineers, and drive cross-functional initiatives.
• Strong communication skills with the ability to explain complex technical topics to non-technical stakeholders.

Compliance and Governance:

• Strong understanding of data governance, CCPA, HIPAA, and compliance requirements. 

Additional Preferred Skills: 

• Experience working in a healthcare or regulated industry (HIPAA/CCPA knowledge a plus).
• Background in MLOps and DevOps best practices.
• Knowledge of automated testing, CI/CD pipelines for ML, and observability tools.

Work Hours and Travel Requirements:

You must be open to assisting in troubleshooting and analysis in the event of off-hours production problems, as needed. The IT Team works in a hybrid environment that requires a minimum of two days per week in the Philadelphia office.

• Health Care Plan (Medical, Dental & Vision)
• Paid Time Off (Vacation, Sick Time Off & Holidays)
• Company Paid Short Term Disability and Life Insurance
• Retirement Plan (401k) with Company Match