AI Solution Architect

Systems Limited; Lahore; On-site; PKR 6,000,000 - 12,000,000; Full time

Job summary

iSystems Ltd. is seeking an experienced Senior Architect to own AI-native application architecture for production systems.

The role focuses on integrating AI capabilities across applications, data, and infrastructure, with leadership in ML engineering and modernization efforts. The ideal candidate has 8+ years in production system architecture, 3+ years in AI-native architectures, and 5+ years in ML engineering at scale.

Qualifications

• 8+ years of experience in production system architecture.
• 3+ years in AI-native application architecture.
• 5+ years of production-scale ML engineering experience.
• Strong expertise in Azure AI Foundry, AWS Bedrock, and Google Vertex AI.
• Experience with Azure ML, AWS SageMaker, and Vertex AI Prediction.
• Knowledge of APIs, microservices, event-driven architecture, API gateways, service mesh, and secure integrations.
• Experience with LangChain, Hugging Face, knowledge graphs, and semantic layers is preferred.
• Deep understanding of AI architecture challenges including latency, non-determinism, scalability, and cost optimization.
• Experience in legacy modernization and AI-native transformation.
• ADR writing and architecture documentation skills.
• Excellent stakeholder management and client-facing communication skills.
• Strong leadership, mentoring, and technical decision-making abilities.

Responsibilities

• Design end-to-end architecture for AI-native applications, including integration, data flow, security, and cost.
• Design AI APIs and services and define how AI capabilities integrate with applications.
• Establish architecture standards, reference patterns, and best practices.
• Lead architecture reviews and identify technical, integration, scalability, and modernization risks.
• Architect production ML pipelines, model serving, retraining, and high-throughput systems.
• Define ML engineering standards covering testing, versioning, and CI/CD.
• Lead root-cause analysis for critical production ML issues.
• Partner with QA/AI Assurance teams to ensure architectural testability.
• Mentor AI Engineers and Developers on architecture and design standards.
• Present and defend architecture decisions to client technical leadership.
• Balance technical best practices with project timelines and delivery requirements.

Skills

Architectural leadership

AI-native architecture

ML engineering

Cloud platforms

API & microservices

ADR/documentation

Stakeholder management

Mentoring

Performance & cost optimization

Tools

Azure AI Foundry

AWS Bedrock

Google Vertex AI

Azure ML

AWS SageMaker

Vertex AI Prediction

Job description

Own the architecture of AI-native applications, ensuring seamless integration across AI capabilities, applications, data, and infrastructure. The role requires 8+ years of experience in architecting production systems, with strong expertise in AI, cloud platforms, ML engineering, and enterprise modernization.

Responsibilities:

• Design end-to-end architecture for AI-native applications, including integration, data flow, security, and cost.
• Design AI APIs and services and define how AI capabilities integrate with applications.
• Establish architecture standards, reference patterns, and best practices.
• Lead architecture reviews and identify technical, integration, scalability, and modernization risks.
• Architect production ML pipelines, model serving, retraining, and high-throughput systems.
• Define ML engineering standards covering testing, versioning, and CI/CD.
• Lead root-cause analysis for critical production ML issues.
• Partner with QA/AI Assurance teams to ensure architectural testability.
• Mentor AI Engineers and Developers on architecture and design standards.
• Present and defend architecture decisions to client technical leadership.
• Balance technical best practices with project timelines and delivery requirements.

Qualifications:

• 8+ years of experience in production system architecture, including 3+ years in AI-native application architecture.
• 5+ years of production-scale ML engineering experience.
• Strong expertise in Azure AI Foundry, AWS Bedrock, and Google Vertex AI.
• Experience with Azure ML, AWS SageMaker, and Vertex AI Prediction.
• Strong knowledge of APIs, microservices, event-driven architecture, API gateways, service mesh, and secure integrations.
• Experience with LangChain, Hugging Face, knowledge graphs, and semantic layers is preferred.
• Deep understanding of AI architecture challenges including latency, non-determinism, scalability, and cost optimization.
• Experience in legacy modernization and AI-native transformation.
• Strong architecture documentation and ADR writing skills.
• Excellent stakeholder management and client-facing communication skills.
• Strong leadership, mentoring, and technical decision-making abilities.