Technical Architect with a strong background in software engineering, data science, and DevOps to lead the design, development, and deployment of scalable machine learning and data science applications. The ideal candidate will have hands-on experience with cloud environments, MLOps, CI/CD pipelines, and multi-tenant architecture. This role requires both technical leadership and the ability to collaborate across cross-functional teams to drive innovation and operational excellence.
1. Solution Architecture & System Design
- Architect scalable, reusable data science and machine learning pipelines leveraging cloud services such as AWS SageMaker, Textract, and Comprehend.
- Design multi-tenant systems with robust application deployment architectures and rate-limiting mechanisms to ensure high availability and performance.
- Translate custom client requirements into scalable technical architecture, conducting impact assessments and delivery planning.
2. Development & Deployment Leadership
- Lead development and deployment of complex data science and information extraction solutions in client cloud environments.
- Manage and optimize CI/CD pipelines for continuous delivery of data science applications.
- Own the tenant onboarding process and manage lifecycle operations for multi-tenant deployments.
3. DevOps & MLOps Management
- Oversee DevOps and MLOps teams to ensure reliable, consistent releases and maintenance of deployed products.
- Collaborate with internal and client DevOps teams to implement best practices and streamline application-specific DevOps workflows.
- Monitor and enhance system performance and operational stability through effective pipeline and infrastructure management.
4. Cross-functional Team Collaboration & Leadership
- Drive collaboration between engineering, data science, delivery, and leadership teams to align technical solutions with business goals.
- Mentor and manage software engineers, DevOps, and MLOps personnel to foster a culture of continuous improvement.
- Represent the technical architecture team in leadership discussions, providing insights and recommendations for strategic decision-making.
5. Stakeholder Engagement & Technical Advocacy
- Act as a key technical advisor during client engagements, translating technical complexities into clear business value propositions.
- Support internal business initiatives, including technical demonstrations, competitions, and strategic presentations.
- Continuously gather feedback to iterate on solutions and drive product innovation.
- Bachelor’s degree in computer science, Information Technology, Business Administration, or related field.
- 7+ years of experience spanning software engineering, data science, and DevOps roles.
- Proven expertise in cloud platforms (AWS preferred), MLOps, and CI/CD pipeline design and management.
- Strong programming skills and hands-on experience with data science application development and deployment.
- Experience managing multi-tenant SaaS or ML platforms.
- Strong leadership, communication, and stakeholder management skills.