• Bachelor’s degree in network engineering, Computer Science, or a related discipline. 

• Minimum 10years of relevant work experience.

• Proven track record of technical leadership

• Possess a solid understanding of foundational machine learning concepts and algorithms and have extensive experience deploying production-grade machine learning solutions

• Possess extensive experience in at least one cloud platform (e.g., AWS, GCP, Azure) and be well-versed in associated machine learning services, such as Amazon SageMaker, Azure ML, and Databricks

• Work with the infrastructure and cloud provisioning teams to implement Azure cloud infrastructure solutions using Infrastructure as Code (IaC) principles and tools 

• Offer technical leadership on high-impact projects, ensuring they meet quality standards and are aligned with the organization's objectives.

• Lead the development, deployment and management ML models into production, ensuring seamless integration with existing systems and monitoring model performance.

• Influence and coach a distributed team of engineers and facilitate alignment and clarity across teams on goals,

• Excellent communication and technical presentation skills

• Able to think strategically and tactically and to build consensus to make programs successful.

• Hands-on experience of 4 - 6 yrs with Python, Django, FastAPI

• Experience of 2-4 yrs in deploying infrastructure as code tools e.g. Azure Bicep or Terraform

• Hands-on experience in one or several of the following areas: Machine Learning, Data Engineering, DevOps and MLOps

• Experience with Azure DevOps for CI/CD, unit testing, and AGILE development

• Exposure working with ML teams and deploying models in domains eg. convex optimization, statistical models, time-series models, and Reinforcement Learning/DRL

• Experience developing and deploying monitoring tools e.g. Elastic search, Grafana

Preferred Job Qualifications: 

• Post-graduate qualifications in Computer Science, Data Engineering or professional qualifications in Advanced Data Design, Big Data. 

• Extensive experience with Azure ML tools and services.   

• Experience in implementing Generative AI solutions. 

• Proven experience designing and managing cloud infrastructure for enterprise applications.

• Expertise in cloud platforms such as AWS or Azure Cloud.

• Strong understanding of security and compliance frameworks.

• Strong knowledge of network architecture, virtualized environments, and security protocols.

• Effective communication and collaboration skills

• Previous experience as Cloud Architect or similar role.

• Excellent problem-solving and analytical skills.

• Working knowledge of agile principles, and experience leading in a Scaled Agile paradigm.

• Medicare/Medicaid knowledge

• Experience with a cloud platform such as AWS and the services available in there to build and host the applications. Key services: S3, Lambda, CloudFront, API Gateway, DynamoDB / RDS, IAM, KMS. Experience with ECS/EKS, Docker and Kubernetes are an advantage.