What you will be doing

• Design and implement scalable, robust cloud-based architectures for AI/ML and automation solutions
• Lead the development of solution architectures, ensuring alignment with business objectives and technical requirements
• Collaborate with cross-functional teams to integrate AI/ML models and automation processes into existing systems
• Optimize cloud infrastructure for performance, cost-efficiency, and security
• Implement containerization strategies and manage Kubernetes clusters for deploying AI/ML workloads
• Drive DevOps practices to streamline development, testing, and deployment processes
• Provide technical leadership and mentorship to development teams
• Evaluate and recommend new technologies and tools to enhance our AI/ML and automation capabilities

What you bring:

Knowledge / Experience

• Extensive experience as a Cloud Solution Architect. Experience in AI/ML and automation projects would be a good-to-have
• Solid background in solution architecture, preferably with Java expertise
• In-depth knowledge of Azure Cloud services, particularly those related to AI/ML and data processing
• Hands-on experience with containerization technologies, especially Docker and Kubernetes/AKS
• Proven track record in implementing DevOps practices and tools
• Experience in designing and implementing scalable, distributed systems
• Familiarity with data storage solutions, both relational and NoSQL databases
• Knowledge of security best practices for cloud-based applications
• Understanding of AI/ML concepts, workflows, and deployment challenges is a good to have

Essential Skills:

• Cloud Architecture: Proficiency in designing and implementing cloud solutions which are saleable, with a focus on Azure Cloud services
• Solution Architecture: Ability to create comprehensive technical solutions that address complex business requirements. Strong understanding of various design pattens, microservices, caching solutions etc.
• Programming: Strong coding skills (preferably in Java, Python)
• Containerization: Expertise in Docker, Kubernetes, and Azure Kubernetes Service (AKS)
• DevOps: Experience with CI/CD pipelines, infrastructure as code, Tools like Jenkins, Harness, Helm charts, Terraform, etc.
• Data Management: Knowledge of data processing pipelines. Extensive experience of working with SQL DBs, data warehouses, etc.
• Security: Understanding of cloud security principles and best practices, OAuth, Entra ID, etc.
• Communication: Excellent verbal and written communication skills to collaborate with technical and non-technical stakeholders
• Problem-solving: Strong analytical and critical thinking skills to address complex architectural challenges
• Leadership: Ability to guide and mentor development teams and influence technical decisions
• AI/ML Technologies: Familiarity with AI/ML and Gen AI is good-to-have

Qualifications

• Software Engineering Degree or equivalent
• Certifications in cloud architecture are good to have.