Key Responsibilities:

· Lead the design and implementation of cloud infrastructure on AWS and Google Cloud Platform with a focus on compute, storage, networking, and AI/ML services.

· Architect and implement scalable, resilient, and secure cloud solutions aligned with business requirements.

· Provide technical leadership and mentorship to engineers, ensuring best practices in architecture, development, and deployment.

· Drive automation and CI/CD pipelines using DevOps tools such as Kubernetes, Jenkins, Docker, Git, Prometheus, and Grafana.

· Collaborate with cross-functional teams including data scientists, software engineers, and product owners to incorporate AI/ML capabilities into cloud solutions.

· Monitor, troubleshoot, and optimize cloud infrastructure performance and security.

· Define and enforce cloud governance, cost management, and operational standards.

· Lead code reviews, design discussions, and technology evaluations.

· Stay current with emerging cloud technologies, identify opportunities for innovation, and provide strategic recommendations.

· Team management and co-ordination with Client , vendor management.

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Required Skills & Experience:

· 12-15 years of overall IT experience with at least 6-8 years in cloud architecture and implementation.

· Expertise in AWS and GCP services including but not limited to:

o Compute: EC2, Lambda, GCE, Google Cloud Functions

o Storage: S3, EBS, Google Cloud Storage, Cloud SQL, BigQuery

o Networking: VPC, Subnets, Load Balancers, Cloud CDN, VPN, Firewall rules

o AI/ML: SageMaker, Google AI Platform, TensorFlow integration, AutoML

· Strong hands-on experience with container orchestration and DevOps tools:

o Kubernetes, Docker, Jenkins, Git, Prometheus, Grafana

· Proficient in scripting and automation using Python, Bash, or similar languages.

· Solid understanding of CI/CD pipelines, infrastructure as code (Terraform, CloudFormation), and monitoring tools.

· Experience in microservices architecture, networking concepts, and security best practices.

· Proven track record of leading and mentoring technical teams in an Agile environment.

· Excellent communication, problem-solving, team management and stakeholder management skills.

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Preferred Qualifications:

· Relevant certifications such as AWS Certified Solutions Architect, Google Professional Cloud Architect, Certified Kubernetes Administrator (CKA) would be added advantage and will be preferred .

· Background in machine learning model deployment and monitoring on cloud platforms.

· Experience with security frameworks and compliance standards (e.g., ISO, SOC2, GDPR).

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What We Offer:

· Opportunity to work on cutting-edge cloud and AI/ML technologies.

· Collaborative environment with talented technologists.

· Competitive compensation and benefits package.

· Opportunities for professional growth and certifications.