Role: AI Architect
Location: San Diego, CA
Full-Time Position
The ideal candidate is a strategic AI leader who has successfully architected and deployed enterprise GenAI solutions using Claude, Gemini, Azure, and AWS, possesses strong executive communication skills, and can bridge business objectives with advanced AI technologies to drive measurable business value.
Position Overview
We are seeking an experienced AI Architect to lead the design, development, and deployment of enterprise-scale Artificial Intelligence and Generative AI solutions. The ideal candidate will possess deep expertise in modern Large Language Models (LLMs), multi-cloud AI platforms, and enterprise architecture, with proven hands-on experience leveraging Anthropic Claude, Google Gemini, Microsoft Azure AI Services, and AWS AI/ML services.
This role will partner with business leaders, engineering teams, data scientists, and cloud architects to define AI strategy, establish architecture standards, and deliver scalable, secure, and responsible AI solutions that drive measurable business outcomes.
Key Responsibilities
AI & GenAI Architecture
Define and implement enterprise AI architecture frameworks, standards, and best practices.
Design end-to-end Generative AI solutions leveraging Claude, Gemini, OpenAI, and other leading foundation models.
Architect Retrieval Augmented Generation (RAG), agentic AI, multi-agent systems, vector databases, and knowledge management solutions.
Develop scalable AI platforms supporting enterprise-wide adoption and governance.
Cloud & Platform Architecture
Architect AI solutions across Azure and AWS environments.
Design secure and scalable AI infrastructure utilizing:
Azure OpenAI Service
Azure AI Foundry
Azure Machine Learning
Azure Cognitive Services
Amazon Bedrock
Amazon SageMaker
AWS AI Services
Establish cloud-native patterns for AI application deployment and operations.
Solution Design & Delivery
Lead technical architecture reviews and solution design workshops.
Translate business requirements into scalable AI and machine learning solutions.
Collaborate with engineering teams to implement production-grade AI systems.
Drive AI adoption through reusable frameworks, accelerators, and reference architectures.
Governance & Responsible AI
Define AI governance, security, compliance, and risk management frameworks.
Implement model monitoring, observability, guardrails, and responsible AI practices.
Ensure solutions comply with enterprise security, privacy, and regulatory requirements.
Leadership & Innovation
Serve as a trusted advisor to executive leadership on AI strategy and emerging technologies.
Mentor architects, engineers, and data science teams.
Evaluate emerging AI technologies and recommend adoption strategies.
Drive innovation initiatives and proof-of-concepts for strategic business opportunities.
Required Qualifications
Experience
10+ years of experience in software engineering, cloud architecture, data platforms, or enterprise architecture.
5+ years of experience designing and implementing AI/ML solutions.
3+ years of experience with Generative AI and Large Language Models in enterprise environments.
Proven experience leading enterprise AI transformations and architecture programs.
Technical Expertise
Foundation Models & GenAI
Demonstrated expertise with:
Anthropic Claude
Google Gemini
OpenAI models
Multi-model orchestration strategies
Experience with prompt engineering, fine-tuning, model evaluation, and AI agent frameworks.
Microsoft Azure
Azure OpenAI Service
Azure AI Foundry
Azure Machine Learning
Azure Kubernetes Service (AKS)
Azure Data Services
Azure Security and Identity solutions
Amazon Web Services
Amazon Bedrock
Amazon SageMaker
AWS Lambda
ECS/EKS
AWS Data and Analytics services
AWS Security and Governance services
AI & Data Technologies
RAG architectures
Vector databases (Pinecone, Weaviate, Milvus, Chroma, Azure AI Search)
LangChain, LangGraph, LlamaIndex
AI Agents and Agentic Workflows
MLOps and LLMOps
Model monitoring and evaluation frameworks
Programming
Python
SQL
REST APIs
Microservices Architecture
CI/CD and DevOps practices
Preferred Qualifications
Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.
Experience with enterprise AI governance and Responsible AI frameworks.
Experience in regulated industries such as healthcare, financial services, defense, or technology.
Experience integrating AI solutions with ERP, CRM, and enterprise systems.
Preferred Certifications
Microsoft Certified: Azure Solutions Architect Expert
Microsoft Certified: Azure AI Engineer Associate
AWS Certified Solutions Architect Professional
AWS Certified Machine Learning Specialty
Google Professional Cloud Architect
Google Professional Machine Learning Engineer
Success Metrics
Delivery of scalable enterprise AI solutions.
Successful deployment of GenAI applications into production.
Adoption of AI platforms and architecture standards across business units.
Improved operational efficiency and business outcomes through AI-driven initiatives.
Establishment of secure, governed, and responsible AI practices.
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