AI Solution Architect

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

Job summary

Systems Limited is seeking an experienced AI-native architect to own the end-to-end design of production AI-enabled systems, ensuring integration across AI capabilities, data, and infrastructure. The role requires 10+ years of experience in architecture with strong expertise in AI, cloud platforms, ML engineering, and enterprise modernization.

You will mentor AI engineers, define standards, and present architecture decisions to client leadership, balancing best practices with delivery timelines

Qualifications

• 8+ years in production system architecture, with 3+ years in AI-native architecture.
• 5+ years in production-scale ML engineering.
• Strong expertise in major cloud AI platforms.
• Experience with APIs, microservices, and secure integrations.
• Proficient in architecture documentation and ADR writing.
• Excellent stakeholder management and client-facing skills.
• Proven leadership and mentoring 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 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 architecture

Cloud platforms

ML engineering

Enterprise modernization

APIs & microservices

ADR writing

Stakeholder management

Leadership

Tools

Azure AI Foundry

AWS Bedrock

Vertex AI

Azure ML

SageMaker

Vertex AI Prediction

LangChain

Hugging Face

Knowledge graphs

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.