Hi
Role : AI Solution Architect – Agentic & Generative AI
Locations: Austin, Tx | Tempe, Az | Charlotte, NC | New York, NY
Role Overview
The AI Solution Architect is a senior technical leader responsible for designing, architecting, and operationalizing Agentic AI and Generative AI solutions at enterprise scale. This role is central to shaping and implementing an AI-first Product Delivery Lifecycle (PDLC), ensuring product development processes, engineering practices, and operating models are optimized for AI-native platforms, agentic systems, and rapid value iteration.
This individual will operate at the intersection of architecture, AI platform engineering, ML lifecycle management, enterprise integration, governance, and organizational transformation.
Key Responsibilities
AI Architecture & Solution Design
Architect enterprise-scale Agentic and Generative AI systems, including:
Multi-agent orchestration frameworks
Retrieval-Augmented Generation (RAG) pipelines
Autonomous task execution patterns
Tool-use integration frameworks
Establish reference architectures for an AI-first PDLC covering:
Design
Development
Testing & evaluation
Deployment
Monitoring & observability
Risk controls & governance
Design and implement model lifecycle pipelines including:
Training & fine-tuning workflows
Evaluation harnesses
Model registry & versioning
Continuous improvement loops
Embed AI capabilities into client-facing platforms, internal tooling, and operational workflows.
AI-First PDLC Transformation
Define architecture, tooling, and standards for an AI-native delivery lifecycle, including:
Prompt engineering frameworks
Agent design patterns
Automated LLM evaluation systems
Safety guardrails and policy enforcement
Data quality validation mechanisms
Integrate AI evaluation and governance gates into CI/CD pipelines.
Establish best practices to enable cross-functional teams to become AI “builders.”
Drive adoption of AI-driven development patterns across product, engineering, design, and risk functions.
Enterprise Integration & Data Strategy
Design integrations between AI systems and core enterprise platforms.
Partner with Data Engineering teams to define:
Data ingestion architectures
Embedding & vectorization strategies
Feature stores
Real-time inference pipelines
Ensure architectural alignment with:
Cloud strategy
Enterprise data governance
Security & compliance standards
Security, Compliance & Responsible AI
Architect AI systems in compliance with regulatory and governance requirements.
Embed identity, authorization, auditing, and model-level security patterns.
Implement Responsible AI practices, including:
Transparency
Bias monitoring
Fairness evaluation
Performance & drift monitoring
Auditability
Cross-Functional Leadership
Partner with senior leaders across Product, Enterprise Architecture, DevSecOps, Infrastructure, and Operations.
Lead architectural reviews and design whiteboarding sessions.
Mentor engineering teams and contribute to AI architecture standards.
Support hiring and talent development for emerging AI roles.
Required Qualifications
2+ years architecting Generative AI, Agentic AI, or ML systems at enterprise scale.
6+ years experience in cloud-native architecture (AWS preferred), including:
Microservices
Kubernetes
Event-driven systems
5+ years hands-on experience with:
LLMs
Vector databases
Embeddings
Evaluation frameworks
Guardrails
Fine-tuning
Orchestration frameworks
8+ years experience in Python.
Proficiency in C#, Java, or TypeScript is a plus.
6+ years experience in ML Ops, including:
CI/CD for ML
Model versioning
Monitoring
Automated evaluation
Preferred Qualifications
Bachelor’s degree in Computer Science, Engineering, AI/ML, or equivalent experience.
Relevant certifications such as:
AWS Solutions Architect – Professional
AWS Machine Learning Specialty
Terraform Associate
Experience in regulated industries.
Experience designing AI systems under compliance constraints.
Core Competencies
Strategic Architecture & Systems Thinking
AI Fluency & Model Lifecycle Expertise
Experimentation & Data-Driven Decision-Making
Cross-Functional Collaboration
Innovation & Continuous Learning
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