> Markdown version of [/jobs/ext/3605919-artificial-intelligence-machine-learning-advisor](https://www.wearedevelopers.com/jobs/ext/3605919-artificial-intelligence-machine-learning-advisor). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Artificial Intelligence & Machine Learning, Advisor - **Company:** Peraton Inc - **Location:** United States - **Experience:** Experienced - **Salary:** $146,000.0 - $234,000.0 - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Artificial Intelligence, Amazon Web Services, Amazon S3, Application Integration Architecture, Confluence, JIRA, Data Security, Fraud Prevention and Detection, Identity and Access Management, Information Retrieval, Python (Programming Language), Machine Learning, Octopus Deploy, Performance Tuning, Standard Sql, Software Engineering, Management of Software Versions, Feature Store, Data Storage Technologies, Retrieval-Augmented Generation, Transfer Learning, Large Language Models, Snowflake, Multi-Agent Systems, Prompt Engineering, Llamaindex, Amazon Virtual Private Cloud (VPC), Agentic-AI, Data Lakes, Deployment Automation, CrewAI, Machine Learning Operations, Restful APIs, Terraform, Databricks - **Published:** October 7, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9222767/artificial-intelligence-machine-learning-advisor ## About the Role * 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. * Has an "AI first" mentality and uses AI to accelerate productivity and software development. * Demonstrated use of AI-driven coding and knowledge of best practices. * Demonstrated experience designing integration architectures for third-party AI tools inside a customer's secure enclave (tenant isolation, identity federation, audit routing) * Working experience with Snowflake and/or Databricks (Unity Catalog, MLflow, Delta Lake) plus strong SQL and Python. * Experience deploying AI/ML workloads on AWS (VPC, IAM, KMS, S3, ECS/EKS, RDS, Bedrock or equivalent) * Solid LLMOps/MLOps practice: versioning, evaluation harnesses, deployment automation, monitoring, governance. * Familiarity with PHI/PII handling and access-controlled data storage. * Strong written and verbal communication; able to present architectures to CMS technical and non-technical stakeholders. * US citizenship; ability to obtain and maintain a Public Trust clearance. Preferred Qualifications: * Databricks E2 experience: Unity Catalog, Feature Store, MLflow registry, REST API integration. * Experience with agentic frameworks such as Strands Agents, LangGraph, LlamaIndex, or CrewAI. * Prior CMS or federal health environment experience (FPS, IDR, One PI). * Knowledge of Medicare/Medicaid claims, NCD policy, and FWA/program-integrity use cases. * Experience with Terraform/IaC, Argo CD, Helm for deploying platform components into AWS/EKS. * Experience with vector databases, hybrid retrieval, graph retrieval, or long-context optimization. * Confluence/JIRA in a SAFe Agile environment. ## Description We are seeking an Artificial Intelligence (AI) Solutions Architect as a senior technical authority on the CMS Fraud Prevention Services (FPS) team, owning the integration architecture that allows three external agentic AI vendors be onboarded into vendor-isolated enclaves inside the FPS ATO boundary. This role will develop AI solutions using Peraton tools to detect fraud, waste, and abuse. Responsibilitie includes the following: * Design the integration architecture for onboarding third-party agentic AI tools into vendor-isolated DISM enclaves inside the FPS ATO boundary. * Author a common data package specification (schema, sampling strategy, PHI/PII handling, refresh cadence, packaging) that every evaluated vendor consumes. * Define the per-vendor integration pattern for data access, identity federation, audit-log routing, and tenant isolation. * Provide deep, hands-on LLM and agentic-AI expertise (RAG, fine-tuning, tool-use/MCP, multi-agent orchestration, LLMOps) to internal Peraton teams and CMS technical stakeholders. * Ensure every architectural design embeds security, quality, PHI/PII, and governance controls appropriate to the FPS environment.