Azure Cloud and AI Lead

Job Title:

Technical Lead – Azure Cloud, Kubernetes & Machine Learning

As a Technical Lead, you will make an impact by designing and delivering scalable, cloud-native solutions that support pricing optimization and IoT-driven business outcomes. You will be a valued member of the engineering team and work collaboratively with architects, product managers, data scientists, and cross-functional technology stakeholders to build secure, reliable, and high-performing platforms.

• Design and implement cloud-native solutions on Azure, ensuring scalability, resiliency, security, and cost efficiency.
• Lead the development and deployment of containerized applications using Kubernetes and modern cloud-native practices.
• Build and enhance backend services using Advanced Java to deliver secure, maintainable, and high-performing business capabilities.
• Develop and support Python-based machine learning and IoT data processing solutions, including model deployment and operationalization.
• Partner with product, architecture, and analytics teams to translate business requirements into technical solutions that drive pricing optimization and measurable business value.

We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a hybrid position requiring 3 days a week in a Cognizant or client office in Toronto, Ontario. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.

The working arrangements for this role are accurate as of the date of posting. This may change based on the project you’re engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.

• 8+ years of experience designing, developing, and implementing enterprise applications using Advanced Java and related frameworks.
• Strong hands-on experience with Microsoft Azure services, including compute, storage, networking, and cloud-native architecture patterns.
• Proven experience deploying and managing microservices-based applications on Kubernetes, including containerization, orchestration, and scaling.
• Strong Python development experience with machine learning, data engineering, and IoT data processing solutions.
• Experience with modern software engineering practices, including CI/CD, automated testing, version control, secure coding, and code reviews.
• Ability to troubleshoot complex production issues across cloud, application, and container platforms.
• Strong communication and stakeholder management skills with experience collaborating across distributed and hybrid teams.

• Azure Solutions Architect Expert, Azure Developer Associate, or similar Microsoft Azure certification.
• Kubernetes or other cloud-native technology certifications.
• Experience implementing observability solutions using logs, metrics, tracing, and monitoring platforms.
• Knowledge of pricing optimization, revenue management, or related analytical business domains.
• Experience working with IoT platforms, real-time data pipelines, and advanced analytics solutions.
• Exposure to machine learning model deployment, MLOps, and production AI environments.

Please note, this role is not able to offer visa transfer or sponsorship now or in the future

Applications will be accepted until August 25, 2025.

The annual salary for this position is between $83,500- $95,500 depending on experience and other qualifications of the successful candidate.

This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.

• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long-term/Short-term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan

The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.