Principal AI Solutions Architect

Role Description

We are seeking an experienced Principal AI Solutions Architect to lead the design and implementation of secure, scalable, and enterprise-grade AI and cloud solutions supporting large-scale 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.

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.

Requirements

• 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 scalable AI adoption and cloud transformation goals.

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 implementing enterprise AI governance and Responsible AI initiatives.
• Familiarity with enterprise modernization and digital transformation initiatives.

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