The Senior Consultant AI/ML will lead the design and delivery of enterprise-scale artificial intelligence solutions, with a particular focus on agentic AI and healthcare claims automation. This fully remote, contract-based opportunity combines advanced AI/ML engineering expertise with strategic consulting and technical leadership. You will serve as a trusted advisor to customer stakeholders, translating complex business challenges into scalable, production-ready AI solutions. A key focus will be automating the entire healthcare claims lifecycle, from intake and adjudication to payments and denial management. Working alongside data scientists, engineers, cloud architects, and healthcare specialists, you will drive implementation using AWS Bedrock AgentCore and related services. This role offers the opportunity to shape enterprise AI strategy, accelerate intelligent automation, and deliver measurable operational improvements across high-volume healthcare processes.
Define and own the AI/ML solution roadmap for end-to-end healthcare claims automation, aligning technical architecture and delivery priorities with enterprise transformation objectives.
Lead customer-facing discussions, technical workshops, and discovery sessions to identify business challenges, assess opportunities, and prioritize agentic AI use cases.
Design and implement scalable AI/ML architectures covering claims intake, data extraction, eligibility verification, medical coding validation, automated adjudication, fraud detection, payment processing, and denial management.
Lead the end-to-end delivery of enterprise AI/ML solutions, taking responsibility for technical execution, project planning, risk management, delivery quality, and stakeholder communication.
Architect and implement agentic AI systems using AWS Bedrock AgentCore Runtime, Strands SDK or equivalent frameworks, and supporting AWS services.
Design and orchestrate agentic AI patterns, including ReAct, tool use, and multi-agent collaboration, to address complex business processes and automate decision-making workflows.
Develop and oversee retrieval-augmented generation (RAG) architectures using Amazon Bedrock Knowledge Bases, vector stores, and relevant data retrieval technologies.
Guide model development, training, validation, deployment, and ongoing optimization throughout the healthcare claims lifecycle.
Establish AI/ML pipelines capable of processing enterprise-scale workloads, including millions of claims per month, while maintaining performance, reliability, scalability, and operational efficiency.
Define and implement AI/MLOps strategies covering model monitoring, retraining pipelines, drift detection, automated testing, and continuous improvement.
Build and manage evaluation frameworks for agentic AI systems, assessing output correctness, safety, latency, cost efficiency, and overall performance.
Implement observability, tracing, monitoring, and debugging capabilities through Amazon Bedrock AgentCore Observability and related tools to ensure system transparency and operational reliability.
Collaborate with data scientists, AI/ML engineers, cloud architects, business analysts, healthcare subject matter experts, and other stakeholders to deliver production-grade solutions.
Ensure AI solutions meet enterprise expectations for security, reliability, maintainability, and responsible implementation while supporting continuous improvement throughout the delivery lifecycle.