Principal AI Solutions Architect

Job Description:

Job Title: Principal AI Solutions Architect Cloud & Enterprise AI

Location: 95% Remote Occasional Onsite Meetings in Washington, D.C.

Position Overview

Patient-Centered Outcomes Research Institute is seeking a highly experienced Principal AI Solutions Architect to lead the design and implementation of secure, scalable, and enterprise-grade AI and cloud solutions supporting healthcare research, data modernization, and digital transformation initiatives.

This role requires deep expertise in AWS cloud architecture, Generative AI ecosystems, enterprise systems integration, MLOps, AI governance, and cloud-native application design. The ideal candidate will serve as a strategic technical leader responsible for architecting AI-enabled platforms while ensuring security, compliance, governance, and operational excellence.

The architect will collaborate closely with enterprise leadership, data engineering teams, cybersecurity, DevSecOps, and application development teams to drive innovation using modern AI technologies including LLMs, RAG architectures, MCP (Model Context Protocol), AI Guardrails, and enterprise AI orchestration frameworks.

Key Responsibilities

Design and implement enterprise-scale AWS cloud architectures supporting AI/ML and GenAI workloads.

Architect Scalable, Resilient, And Secure Cloud-native Solutions Using:

Microservices

Containers

APIs

Event-driven architectures

Serverless computing

Lead Architecture And Integration Efforts For:

Generative AI platforms

LLM orchestration

AI agents

RAG pipelines

Vector databases

Knowledge graph integrations

Design And Implement AI Governance Frameworks Including:

Responsible AI

AI Guardrails

Model monitoring

Risk management

Compliance controls

Implement and support MCP (Model Context Protocol) integrations and AI interoperability solutions.

Architect Enterprise MLOps Pipelines For:

Model training

Validation

Deployment

Observability

Lifecycle management

Design Secure AI Solutions Leveraging AWS Services Such As:

SageMaker

Bedrock

Lambda

ECS/EKS

API Gateway

DynamoDB

S3

IAM

CloudWatch

Collaborate With DevSecOps Teams To Implement:

CI/CD pipelines

Infrastructure as Code (Terraform/CloudFormation)

Security automation

Compliance scanning

Develop architecture standards, governance models, and technical roadmaps.

Provide technical leadership, mentoring, and architectural guidance across engineering teams.

Evaluate emerging AI technologies and recommend enterprise adoption strategies.

Support enterprise modernization initiatives aligned with healthcare and research data platforms.

Required Qualifications

10+ years of experience in:

Enterprise Architecture

Cloud Engineering

Systems Architecture

Solution Architecture

5+ years of hands-on AWS cloud architecture experience.

Strong Expertise In:

AI/ML architecture

Generative AI

Large Language Models (LLMs)

AI orchestration frameworks

MLOps

Experience With:

MCP (Model Context Protocol)

AI Guardrails

Responsible AI frameworks

Strong Experience Designing:

Distributed systems

Enterprise integrations

Cloud-native platforms

Expertise In:

API architecture

Event-driven systems

Kubernetes

Docker

Serverless computing

Experience With Infrastructure As Code:

Terraform

CloudFormation

Strong DevSecOps and CI/CD implementation experience.

Strong Understanding Of:

Security architecture

Governance

Compliance

Enterprise cloud controls

Strong communication and stakeholder management skills.

Preferred Qualifications:

AWS Certified Solutions Architect Professional

AWS AI/ML Specialty Certification

Experience With:

LangChain

OpenAI APIs

Bedrock Agents

Vector databases

Knowledge Graphs

RAG architectures

Experience Supporting Healthcare, Research, Nonprofit, Or Federal Organizations Preferred.

Experience implementing enterprise AI governance and Responsible AI initiatives.

Familiarity with healthcare data modernization and interoperability standards is a plus.

Technical Skills:

AWS Cloud Architecture

Generative AI / GenAI

LLM Integration

MCP (Model Context Protocol)

AI Guardrails

Responsible AI

MLOps

Terraform / CloudFormation

Kubernetes / Docker

Python

API Design

DevSecOps

CI/CD Pipelines

Enterprise Systems Integration

Data & AI Governance

RAG Architectures

Vector Databases

Bedrock / SageMaker

Work Environment

95% Remote

Occasional onsite meetings in Washington, D.C.

Collaborative enterprise architecture and innovation environment

Opportunity to lead next-generation AI transformation initiatives