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 over eight years of experience in architecting production systems, with deep expertise in AI, cloud platforms, machine learning engineering, and enterprise modernization. This role demands a strategic thinker who can balance technical excellence with practical delivery timelines while mentoring teams and collaborating closely with stakeholders.

Key Responsibilities:
- Design comprehensive end-to-end architecture for AI-native applications, covering integration, data flow, security, and cost management.
- Develop AI APIs and services, defining how AI capabilities integrate with broader application ecosystems.
- Establish and enforce architecture standards, reference patterns, and industry best practices.
- Lead architecture reviews to identify and mitigate technical, integration, scalability, and modernization risks.
- Architect production-scale machine learning pipelines, including model serving, retraining, and high-throughput systems.
- Define and implement ML engineering standards related to testing, versioning, and continuous integration/continuous deployment (CI/CD).
- Conduct root-cause analysis for critical production ML issues to ensure system reliability.
- Drive initiatives focused on legacy system modernization toward AI-native architectures.
- Collaborate with QA and AI Assurance teams to ensure architectural testability and quality.
- Mentor AI engineers and developers on architecture and design standards, fostering technical growth.
- Present and defend architectural decisions to client technical leadership, ensuring alignment and buy-in.
- Balance adherence to technical best practices with project timelines and delivery requirements to achieve optimal outcomes.

Required Qualifications:
- Minimum of 8 years’ experience in production system architecture, with at least 3 years focused on AI-native application architecture.
- Over 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.
- Practical experience using Azure ML, AWS SageMaker, and Vertex AI Prediction services.
- In-depth knowledge of APIs, microservices, event-driven architectures, API gateways, service mesh, and secure integration patterns.
- Proven ability to address AI architecture challenges including latency, non-determinism, scalability, and cost optimization.
- Experience leading 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.
- Demonstrated leadership, mentoring, and technical decision-making expertise.

Preferred Qualifications and Benefits:
- Familiarity with LangChain, Hugging Face, knowledge graphs, and semantic layers is highly desirable.
- Opportunity to work on cutting-edge AI-native modernization projects within a collaborative and innovative environment.
- Engage with diverse teams and clients, enhancing leadership and technical influence across multiple domains.

This role offers a unique opportunity to shape the future of AI-driven enterprise applications, combining deep technical expertise with strategic leadership. If you are passionate about AI architecture and driving impactful modernization initiatives, this position will allow you to make a significant contribution.