AI Solution Architect

We are seeking a seasoned architect to lead the design and implementation of AI-native applications, ensuring seamless integration across AI capabilities, applications, data, and infrastructure. The ideal candidate will have extensive experience in architecting production systems with a strong focus on AI, cloud platforms, machine learning engineering, and enterprise modernization. This role demands a strategic thinker who can balance technical excellence with project delivery timelines while driving innovation and modernization initiatives.

Key Responsibilities

Design and oversee the end-to-end architecture of AI-native applications, addressing integration, data flow, security, and cost efficiency. Develop AI APIs and services, defining how AI capabilities integrate with various applications to deliver robust solutions. Establish and maintain architecture standards, reference patterns, and best practices to ensure consistency and quality across projects.

Lead architecture reviews to identify and mitigate technical, integration, scalability, and modernization risks. Architect production machine learning pipelines, including model serving, retraining processes, and high-throughput systems to support scalable AI solutions. Define and enforce ML engineering standards covering testing, versioning, and continuous integration/continuous deployment (CI/CD) practices.

Drive root-cause analysis for critical production ML issues, ensuring rapid resolution and system reliability. Spearhead legacy-to-AI-native modernization initiatives to transform existing systems and leverage AI capabilities effectively. Collaborate closely with QA and AI Assurance teams to ensure architectural testability and quality throughout the development lifecycle.

Mentor AI engineers and developers on architecture and design standards, fostering technical growth and knowledge sharing. Present and defend architectural decisions to client technical leadership, effectively communicating complex technical concepts. Balance adherence to technical best practices with project timelines and delivery requirements to achieve optimal outcomes.

Required Qualifications

A minimum of 8 years of experience in production system architecture, including at least 3 years focused on AI-native application architecture. At least 5 years of hands-on experience in production-scale machine learning engineering. Strong expertise with major cloud AI platforms such as Azure AI Foundry, AWS Bedrock, and Google Vertex AI.

Proven experience working with Azure ML, AWS SageMaker, and Vertex AI Prediction services. Deep knowledge of APIs, microservices, event-driven architecture, API gateways, service mesh, and secure integration techniques. Solid understanding of AI architecture challenges, including latency, non-determinism, scalability, and cost optimization.

Demonstrated experience in legacy modernization and AI-native transformation projects. Excellent skills in architecture documentation and Architecture Decision Records (ADR) writing. Strong stakeholder management capabilities with excellent client-facing communication skills. Proven leadership, mentoring, and technical decision-making abilities.

Preferred Qualifications

Familiarity with LangChain, Hugging Face, knowledge graphs, and semantic layers is highly desirable, enhancing the ability to build advanced AI-driven solutions.

This role offers the opportunity to work at the forefront of AI architecture, driving innovation and modernization in complex enterprise environments. If you are passionate about shaping the future of AI-native applications and have the expertise to lead large-scale, production-grade systems, we encourage you to apply.