AI Solution Architect

Systems Limited; Lahore; On-site; PKR 4,000,000 - 7,000,000; Full time

Job summary

Systems Limited is seeking an experienced architect to own the design of AI-native applications, ensuring seamless integration across AI capabilities, apps, data, and infrastructure.

The role requires 10+ years of production system architecture experience with strong AI, cloud, ML engineering, and modernization expertise. You will mentor engineers, lead architecture reviews, and collaborate with client leadership to balance timing and technical excellence.

Qualifications

• 10+ years of experience in architecting production systems.
• 3+ years in AI-native application architecture.
• 5+ years of production-scale ML engineering.

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

AI-native architecture

Cloud platforms

ML engineering

API design

Leadership

Stakeholder management

ADR writing

Tools

Azure AI Foundry

AWS Bedrock

Vertex AI

Azure ML

SageMaker

LangChain

Hugging Face

Knowledge graphs

Semantic layers

Job description

Own the architecture of AI-native applications, ensuring seamless integration across AI capabilities, applications, data, and infrastructure. The role requires 10+ 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.