Job Description
As a Senior Solution Architect, you will be embedded within the Product Team, leading the architectural evolution of an enterprise Azure Model-as-a-Service (MaaS) platform.
You will define end-to-end solution architectures for AI model hosting, deployment, distribution, and retraining while collaborating closely with engineering teams and customer stakeholders.
This role is not focused on hands-on software development. Instead, you will provide technical leadership, guide architectural decisions, produce high-quality design documentation, and help shape the long-term product roadmap.
You will operate in a fast-paced environment where many design decisions are still evolving, making critical thinking, adaptability, and strong stakeholder management essential for success.
Key Responsibilities
- Design and evolve the architecture of an enterprise Azure Model-as-a-Service (MaaS) platform.
- Define scalable solutions for AI model hosting, deployment, serving, and lifecycle management.
- Drive the platform's expansion into Azure Databricks and Microsoft Fabric for automated model retraining.
- Collaborate closely with Product Managers, Engineering teams, and customer stakeholders to shape product capabilities.
- Translate business requirements into secure, scalable, and maintainable cloud architectures.
- Produce high-quality architecture documentation, technical designs, and solution diagrams.
- Lead technical discussions, identify architectural risks, and challenge assumptions where necessary.
- Guide engineering teams on implementation approaches while ensuring alignment with architectural standards.
- Present solution proposals and value propositions to customers and senior stakeholders.
- Ensure solutions follow best practices for cloud security, networking, scalability, and operational excellence.
- Support CI/CD and deployment strategies for machine learning artifacts across multiple environments.
Required Skills & Experience
- 6+ years of experience as a Solution Architect, Cloud Architect, or Enterprise Architect.
- Strong experience designing solutions on Microsoft Azure.
- Hands-on architectural knowledge of:
- Azure Kubernetes Service (AKS)
- Kubernetes
- Docker and container technologies
- Experience with one or more of:
- Azure Databricks
- Microsoft Fabric
- Azure Machine Learning (Azure ML)
- Solid understanding of MLOps, Machine Learning Development Lifecycle (MDLC), or model-serving architectures.
- Knowledge of the complete machine learning deployment lifecycle, including:
- Model training
- Artifact management
- API-based model serving
- Model lifecycle management
- Experience designing and supporting CI/CD pipelines, preferably using GitLab, including artifact promotion across environments.
- Understanding of cloud networking and security fundamentals, including:
- Ingress and egress management
- Identity and access controls
- Credential management
- Data isolation
- Working knowledge of Python sufficient to understand machine learning documentation and communicate effectively with data scientists and engineers.
- Excellent documentation skills with the ability to create clear architecture designs and technical diagrams.
- Strong communication and presentation skills with experience interacting directly with customers and senior stakeholders.
- English level: C1 (Mandatory).
Nice to Have
- Experience within Financial Services, Capital Markets, or Market Data environments.
- Familiarity with financial data platforms such as:
- Experience working in regulated or audited environments.
- Background in quantitative analysis, statistics, or data science.
- Experience collaborating with data scientists and machine learning engineering teams.
