Senior Consultant AI/ML

Accountabilities:

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.
Requirements:
More than 10 years of experience in technology delivery, including at least five years leading AI/ML programmes at enterprise scale.
Extensive experience designing, developing, and deploying production-grade AI/ML solutions, with a proven track record of leading complex technology initiatives from strategy through implementation.
Strong expertise in agentic AI architectures, including ReAct patterns, tool calling, multi-agent orchestration, and autonomous workflow design.
Hands-on experience with AWS AI services, particularly Amazon Bedrock AgentCore Runtime, and familiarity with the Strands SDK or equivalent agent development frameworks.
Demonstrated ability to design and implement RAG architectures using Amazon Bedrock Knowledge Bases, vector databases, and related retrieval technologies.
Strong understanding of AI/ML engineering principles, including model development, training, evaluation, validation, deployment, and performance optimization.
Experience designing AI/ML and MLOps pipelines, including model monitoring, drift detection, automated retraining, testing, and production operations.
Familiarity with AI observability and evaluation practices, including tracing, debugging, safety assessments, latency measurement, and cost optimization for agentic systems.
Experience delivering scalable cloud-based AI solutions capable of supporting high-volume enterprise workloads, with strong architectural judgement and a focus on production reliability.
Knowledge of healthcare claims processing and related workflows, including claims intake, eligibility verification, medical coding, adjudication, fraud detection, payments, and denial management, is highly relevant to the role.
Ability to translate complex business requirements into practical AI architectures, technical specifications, and implementation roadmaps.
Strong customer-facing consulting skills, with the ability to facilitate technical workshops, influence stakeholders, communicate architectural decisions, and act as a trusted technical advisor.
Demonstrated programme leadership capabilities, including delivery planning, risk management, cross-functional coordination, and accountability for project outcomes.
Excellent analytical, problem-solving, and communication skills, with the ability to balance technical depth, business priorities, and operational requirements.
Ability to work effectively with distributed, multidisciplinary teams in a fully remote environment and manage competing priorities while maintaining high delivery standards.
Benefits:
Fully remote work: Flexibility to work remotely from Anywhere.
Contract-based opportunity: An opportunity to contribute to a major enterprise AI/ML transformation initiative.
Enterprise-scale impact: The chance to develop AI solutions designed to automate healthcare claims processing at a scale of millions of claims per month.
Advanced AI technologies: Hands-on exposure to agentic AI, AWS Bedrock AgentCore, Strands SDK or equivalent frameworks, RAG architectures, and enterprise AI/ML operations.
Technical leadership: Opportunity to shape AI/ML architecture, establish implementation standards, and influence strategic technology decisions.
Cross-functional collaboration: Work alongside AI/ML engineers, data scientists, cloud architects, healthcare specialists, and business stakeholders.
Professional development: Opportunities to deepen expertise in intelligent automation, AI orchestration, model operations, and production-scale AI deployment.