AI Solution Architect

 

 

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