Artificial Intelligence & Machine Learning Advisor

Peraton

. Serve as senior technical authority on the CMS Fraud Prevention Services (FPS) team .

Posted 10/6/2026full-timeUnited StatesMid-LevelSenior💰 $146,000 - $234,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in LLM architectures and agentic AI systems, with a strong focus on integration architecture and security within vendor-isolated environments. Proficient in deploying AI/ML workloads on AWS and ensuring compliance with PHI/PII handling and governance controls.

Highest-signal resume keywords

LLM Architecture ExpertiseAgentic AI SystemsIntegration Architecture DesignAWS Deployment ExperiencePHI/PII Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Fine-Tuning (LoRA/PEFT)RAGPrompt EngineeringTool-Use/MCPMulti-Agent OrchestrationSQLPythonVersioningDeployment AutomationMonitoring

Soft Skills

Strong Written CommunicationStrong Verbal CommunicationAdaptability

Tools & Technologies

SnowflakeDatabricksAWSTerraformArgo CDHelmConfluenceJIRA

Certifications & Qualifications

Public Trust Clearance

Industry Keywords

CMS Fraud Prevention ServicesMedicare/Medicaid ClaimsNCD PolicyFWA/Program-Integrity Use CasesSAFe Agile Environment

Tech Stack

Tools & technologies

AWSPythonSQLTerraformUnity

About the role

Key responsibilities & impact

Serve as senior technical authority on the CMS Fraud Prevention Services (FPS) team
Own integration architecture for onboarding three external agentic AI vendors into vendor-isolated enclaves inside the FPS ATO boundary
Develop AI solutions using Peraton tools to detect fraud, waste, and abuse
Design integration architecture for third-party agentic AI tools in vendor-isolated DISM enclaves inside the FPS ATO boundary
Author a common data package specification covering schema, sampling strategy, PHI/PII handling, refresh cadence, and packaging
Define per-vendor integration patterns for data access, identity federation, audit-log routing, and tenant isolation
Provide hands-on LLM and agentic-AI expertise, including RAG, fine-tuning, tool-use/MCP, multi-agent orchestration, and LLMOps, to internal Peraton teams and CMS technical stakeholders
Ensure architectural designs embed security, quality, PHI/PII, and governance controls appropriate to the FPS environment

Requirements

What you’ll need

Minimum of 8 years with BS/BA; Minimum of 6 years with MS/MA; Minimum of 3 years with PhD
Deep hands-on expertise with LLM architectures and agentic AI systems: fine-tuning (LoRA/PEFT), RAG, prompt engineering, tool-use/MCP, multi-agent orchestration
Ability to be highly independent and adaptive in a fast-changing environment
“AI first” mentality and use of AI to accelerate productivity and software development
Demonstrated use of AI-driven coding and knowledge of best practices
Experience designing integration architectures for third-party AI tools inside a customer's secure enclave, including tenant isolation, identity federation, and audit routing
Working experience with Snowflake and/or Databricks, plus strong SQL and Python
Experience deploying AI/ML workloads on AWS, including VPC, IAM, KMS, S3, ECS/EKS, RDS, and Bedrock or equivalent
Solid LLMOps/MLOps practice: versioning, evaluation harnesses, deployment automation, monitoring, and governance
Familiarity with PHI/PII handling and access-controlled data storage
Strong written and verbal communication; ability to present architectures to CMS technical and non-technical stakeholders
US citizenship
Ability to obtain and maintain a Public Trust clearance
Preferred: Databricks E2 experience, including Unity Catalog, Feature Store, MLflow registry, and REST API integration
Preferred: Experience with agentic frameworks such as Strands Agents, LangGraph, LlamaIndex, or CrewAI
Preferred: Prior CMS or federal health environment experience
Preferred: Knowledge of Medicare/Medicaid claims, NCD policy, and FWA/program-integrity use cases
Preferred: Experience with Terraform/IaC, Argo CD, and Helm for AWS/EKS platform deployment
Preferred: Experience with vector databases, hybrid retrieval, graph retrieval, or long-context optimization
Preferred: Confluence/JIRA in a SAFe Agile environment