AI Architect

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.