• Architect and maintain AWS demo environments using services such as EC2, ECS/Fargate, Lambda, S3, RDS, DynamoDB, IAM, KMS, API Gateway, CloudWatch, and AWS Glue. • Develop Python-based solutions leveraging libraries like NumPy, Pandas, Scikit-learn, and others for data processing and automation. • Build and manage Terraform modules for automated provisioning, environment resets, and decommissioning. • Integrate AWS GenAI services (Bedrock, SageMaker) for real-time demo enrichment and scenario automation. • Collaborate with Demo COE and Product SMEs to design and implement custom demo flows. • Implement RBAC, feature toggles, and configuration management using AWS Systems Manager and AppConfig. • Ensure environmental health through automated monitoring, alerting, and load testing (CloudWatch, ALB, X-Ray). • Support automated QA gates, metrics collection, and post-demo knowledge management. • Provide secondary support for data engineering tasks (AWS Glue, Redshift, Athena) for ingestion and transformation. • Contribute to hybrid cloud demos and integrations with Azure as needed.

• API integrations connecting 10+ live business tools • AI assistants powered by Claude (Anthropic) for internal automation • Auto-billing systems that save hours every month • Real-time dashboards pulling data from multiple platforms • Whatever you dream up that makes us more efficient

• Define and execute the AI engineering strategy and technical roadmap, ensuring alignment with Lantern’s product, clinical, and business priorities. • Build, lead, and scale a high-performing AI engineering team, including hiring, mentoring, performance management, and creating a culture of technical excellence and innovation. • Drive rapid AI proof-of-concept development, moving from problem identification to working prototypes on aggressive timelines, and shepherding successful POCs into production-grade systems. • Own the end-to-end lifecycle of ML/LLM systems—from research and experimentation through production deployment, monitoring, and continuous improvement. • Establish and maintain best-in-class MLOps practices: experiment tracking, reproducibility, CI/CD for models, automated testing, drift detection, observability, and scalable infrastructure on Azure. • Partner with product, clinical operations, marketing, data, and engineering leadership to identify high-impact AI opportunities and translate them into well-scoped, executable initiatives. • Lead architecture decisions for ML/LLM systems, ensuring scalability, reliability, security, and compliance with healthcare regulations. • Establish clear KPIs and success metrics for the AI engineering function, including model performance, delivery velocity, team health, and business impact. • Champion responsible AI practices across the organization, including fairness, transparency, explainability, and regulatory compliance in healthcare contexts. • Represent the AI engineering function to executive leadership, providing regular updates on progress, risks, and strategic recommendations. • Build external visibility for Lantern’s AI capabilities through thought leadership, community engagement, and talent brand building.

• Design and implement the next generation of GenAI-powered business solutions. • Collaborate closely with key stakeholders to translate both business and technical requirements into actionable solutions. • Develop diagrams, models, and documentation to support design, integration, and delivery. • Work with senior architects on complex system integrations.