The consultant will lead the end-to-end delivery of enterprise-scale AI/ML solutions for healthcare claims automation. They are responsible for architecting AI pipelines, defining roadmaps, and managing cross-functional teams to ensure production-grade deployment.
Senior Consultant AI/ML 100% Remote
10+ years in technology delivery with 5+ years leading AI/ML programs at enterprise scale to serve as the Subject Matter Expert for the Agentic AI workstream. This resource will lead customer-facing conversations to understand use cases, design agentic AI solutions, and drive implementation using AWS Bedrock AgentCore and supporting services. The consultant must combine deep AI/ML engineering expertise with the ability to act as a trusted technical advisor to customer stakeholders. The consultant will own end-to-end delivery of an enterprise-scale AI/ML solution that fully automates the healthcare claims processing lifecycles from claims intake and adjudication through payment and denial management. This role requires a blend of technical depth in AI/ML, healthcare domain expertise, and strong program leadership to drive transformation at scale.
Define and own the AI/ML solution roadmap for end-to-end claims automation, aligning with the customer’s enterprise transformation goals
Work with cross-functional teams (data scientists, AI/ML engineers, cloud architects, business analysts, and SMEs) to deliver production-grade AI/ML solutions
Serve as the primary point of accountability for project delivery, risk management, and stakeholder communication
Architect the AI/ML pipeline: claims intake , data extraction, eligibility verification, medical coding validation, auto-adjudication, fraud detection, and payment processing
Oversee model development, training, validation, and deployment across the claims lifecycle
Ensure solution scalability to handle enterprise-level claim volumes (millions of claims/month)
Define AI/MLOps strategy including model monitoring, retraining pipelines, drift detection, and testing
Lead technical workshops with customer to identify, prioritize, and scope agentic AI use cases
Design agentic patterns (ReAct, tool-use, multi-agent orchestration) mapped to customer business problems
Build and operate evaluation pipelines for agentic systems (correctness, safety, latency, cost)
Implement agents using Strands SDK (or equivalent) with Bedrock AgentCore Runtime
Design and implement RAG architectures using Bedrock Knowledge Bases and vector stores
Instrument agents for tracing, monitoring, and debugging via Bedrock AgentCore Observability
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