Job Description
🏢 Hiring via aiRecruitTalent
🤖 Industry: Artificial Intelligence | Enterprise Technology | Cloud | Software
Our client is seeking an experienced AI Solution Architect to design and deliver scalable, secure, production-grade AI solutions for enterprise and global use cases.
This is an excellent opportunity for a technically strong architect who can translate complex business requirements into practical AI architectures and work closely with engineering, data, security, and business teams to move AI initiatives from concept to production.
Modern AI architecture roles increasingly require hands-on expertise across LLMs, RAG, agentic systems, cloud platforms, APIs, MLOps/LLMOps, security, and enterprise integration.
🌟 About the Role
As the AI Solution Architect, you will own the technical architecture of AI-powered solutions, ensuring they are scalable, secure, reliable, cost-effective, and aligned with business objectives.
You will work across the complete solution lifecycle — from discovery and architecture through development, deployment, integration, and production optimization.
🔑 Key Responsibilities
AI Solution Architecture
Design end-to-end architectures for AI, Generative AI, and machine learning solutions.
Translate business requirements into scalable technical architectures.
Develop architecture blueprints, system designs, data flows, APIs, and integration models.
Define build, buy, or integrate strategies for AI capabilities.
Generative AI & LLM Architecture
Design production-grade solutions using LLMs, RAG, AI agents, and intelligent automation.
Evaluate foundation models and select appropriate models for specific use cases.
Design prompt, context, retrieval, orchestration, and tool-calling architectures.
Establish approaches for AI evaluation, observability, reliability, and optimization.
Cloud & Infrastructure
Architect secure AI workloads across AWS, Microsoft Azure, and/or Google Cloud.
Design cloud-native architectures using containers and Kubernetes where appropriate.
Develop scalable data and AI infrastructure.
Optimize AI workloads for performance, availability, security, and cost.
MLOps / LLMOps
Define production deployment and lifecycle management strategies for AI systems.
Establish CI/CD, monitoring, model evaluation, retraining, and observability practices.
Support reliable transition from prototypes to production systems.
Enterprise Integration
Integrate AI solutions with enterprise applications, APIs, databases, CRM, ERP, workflow platforms, and data systems.
Design secure integration and identity architectures.
Ensure AI solutions can operate effectively within existing enterprise environments.
Security & Governance
Incorporate security, privacy, compliance, and responsible AI principles into solution architecture.
Establish appropriate access controls, encryption, data protection, and monitoring.
Ensure AI solutions meet enterprise governance requirements.
Technical Leadership
Work closely with AI engineers, software engineers, data scientists, DevOps, cybersecurity, and product teams.
Provide technical direction throughout implementation.
Mentor engineering and architecture teams.
Present architecture decisions and technical recommendations to senior stakeholders.
Requirements
https://www.airecruittalent.com/jobs/b6584b25-9a5e-4b54-9c00-e9ec0ba8605a
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