Assistant Vice President

EXL

. Own end-to-end technical architecture for AI-powered healthcare solutions, including agent orchestration, LLM serving, retrieval pipelines, data ingestion, and legacy payer-system integration .

Posted 9/19/2026full-timeUnited StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and deploying AI-powered healthcare solutions, with a strong focus on multi-agent systems, cloud architecture, and compliance with healthcare regulations. Proficient in hands-on development and integration of AI technologies within client environments, ensuring secure and scalable implementations.

Highest-signal resume keywords

AI Architecture and DeploymentMulti-Agent System DesignCloud Architecture (Azure, AWS, GCP)Healthcare Payer Operations ExpertiseHands-On AI Solution Development

ATS Keywords

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Hard Skills

AI Solution ArchitectureLLM DevelopmentPython ProgrammingInfrastructure-as-CodeDocker/KubernetesCI/CD PracticesMLOps/LLMOpsPrompt EngineeringData IngestionAPI Design

Soft Skills

Client EngagementTeam LeadershipProblem SolvingCommunicationAdaptability

Tools & Technologies

Azure OpenAIAWS BedrockGCP Vertex AILangChainLangGraphCrewAIAutoGenMCGInterQualQNXT

Certifications & Qualifications

Azure Solutions ArchitectAWS Solutions Architect ProfessionalGCP Professional Architect

Industry Keywords

Healthcare CompliancePHI De-IdentificationHL7FHIRX12 EDIPrior AuthorizationUtilization ManagementCare ManagementClaims ProcessingCMS Regulatory Frameworks

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformKubernetesPython

About the role

Key responsibilities & impact

Own end-to-end technical architecture for AI-powered healthcare solutions, including agent orchestration, LLM serving, retrieval pipelines, data ingestion, and legacy payer-system integration
Define and maintain reusable reference architectures, design patterns, and architectural guardrails for Agentic AI solutions
Establish and govern AI Dev/QA/Prod environments, CI/CD pipelines, and MLOps/LLMOps practices
Embed within client environments to understand workflows, data, constraints, and edge cases
Personally build, configure, deploy, troubleshoot, and harden AI solutions inside client infrastructure
Prototype, demonstrate, gather feedback, and rapidly move solutions into production
Capture reusable learnings, accelerators, and intellectual property from deployments
Architect secure, scalable multi-cloud and hybrid deployments across Azure, AWS, and GCP
Build infrastructure-as-code and Docker/Kubernetes deployments, plan GPU capacity, and optimize LLM cost and latency
Implement AI gateways, PHI de-identification layers, and enterprise integration patterns
Ensure resilient, observable deployments meet stress and throughput targets
Architect and build multi-agent systems with human-in-the-loop governance
Set standards for prompt engineering, RAG pipelines, fine-tuning/domain adaptation, embeddings, and vector search
Build agent execution layers for legacy systems using MCP servers and browser/desktop automation
Champion explainability-first, audit-ready AI design for CMS audits and payer compliance reviews
Apply payer workflow expertise across Prior Authorization, Utilization Management, Care Management, Claims, and Provider operations
Integrate AI solutions with MCG, InterQual, CMS medical policies, QNXT, Facets, and CareRadius using HL7, FHIR, and X12 EDI
Support CMS-0057-F interoperability and prior-authorization mandates
Champion privacy-first design, data anonymization, and HIPAA/PHI/PII compliance
Establish AI controls for model monitoring, bias detection, drift management, and human-in-the-loop overrides

Requirements

What you’ll need

Bachelor’s degree in computer science, Engineering, Data Science, or a related technical field
Master's degree (M.Tech / MS / MBA) preferred
10+ years of progressive experience in software/AI engineering, cloud architecture, or forward deployed/solution engineering roles
Proven hands-on architecture and deployment across at least one major hyperscaler (Azure / AWS / GCP), including production-grade, secure, scalable systems in client environments
Demonstrated design and delivery of Agentic AI / multi-agent and Generative AI systems (LLMs, RAG, orchestration frameworks) in production
Strong understanding of U.S. healthcare payer operations (Prior Auth, UM, Care Management, or Claims)
Proven track record of personally taking AI solutions from POC to live production—hands-on, not purely advisory
Hands-on and architectural expertise in LLMs, embeddings, vector search, prompt engineering, and RAG pipelines
Strong coding ability (Python and related AI/ML stacks)
Proficiency with Azure OpenAI, AWS Bedrock (Claude/Sonnet), and GCP Vertex AI
Expertise with LangChain, LangGraph, CrewAI, AutoGen, or equivalent
Strong understanding of MCP (Model Context Protocol), A2A protocols, and multi-agent system design
Experience with infrastructure-as-code, Docker/Kubernetes, CI/CD, MLOps/LLMOps, and GPU capacity planning
Experience with secure API design, OAuth2/JWT, enterprise integration patterns, and healthcare data standards (HL7, FHIR, X12 EDI 837/835/270/271/276/277)
Deep understanding of payer clinical and claims workflows and integration with QNXT, Facets, or CareRadius
Familiarity with MCG, InterQual, and CMS regulatory frameworks, including CMS-0057-F
Comfortable being embedded on-site/in client environments with significant travel
Ability to lead distributed U.S. and offshore engineering support while remaining hands-on
Preferred: experience building AI Centers of Excellence or reusable healthcare agent frameworks/accelerators
Preferred: patent holder, published researcher, or recognized contributor in AI/healthcare innovation
Preferred: experience with Databricks, Snowflake, or similar data platforms in healthcare
Preferred: cloud/AI certifications such as Azure Solutions Architect, AWS Solutions Architect Professional, or GCP Professional Architect

Benefits

Comp & perks

Work From Home
Significant travel and direct, day-to-day collaboration with client technical teams
Opportunity to work on Agentic AI and Generative AI solutions for large U.S. healthcare payers