Senior Engineer - Cloud & AI

We are seeking a "Senior Engineer - Cloud and AI" to drive the development through the deployment of cutting-edge cloud-native AI solutions. This role requires a combination of deep technical expertise in Microsoft Azure, strong DevOps and CI/CD practices, and an engineering mindset focused on delivering impactful and value-centric solutions. The ideal candidate is a collaborative team player who thrives in both research-oriented problem solving and timeline-driven execution. The individual comes with a proven background in deploying Generative AI workloads (LLM's, LVMs, TTS, Speech to Text, etc. ), cloud native, with Security by design using Commercial (for example: Azure OpenAI), or Open-source (for example: Llama, Mistral, etc. ) models.

Responsibilities:

• Drive the design, development, and deployment of cloud-native Generative AI solutions on Microsoft Azure.
• Implement and maintain DevOps best practices, including CI/CD pipelines, Infrastructure as Code (IaC), and version control using GitHub or Azure DevOps.
• Collaborate with data scientists, AI/ML teams, and business stakeholders to deploy and optimise AI models within cloud-native architectures, ensuring seamless integration and performance at scale.
• Drive cloud architecture decisions in partnership with Enterprise Architecture, TechOps, and Cybersecurity functions, ensuring scalability, security, and cost efficiency.
• Build and manage CI/CD pipelines to streamline the deployment process and ensure rapid delivery of high-quality applications.
• Advocate and implement Infrastructure as Code (IaC) to automate infrastructure provisioning, ensuring consistency across environments.
• Collaborate closely with cross-functional teams, promoting a culture of teamwork and innovation.
• Provide technical leadership, mentor team members, and foster a continuous learning environment.
• Stay up to date with the latest trends in Azure services, AI technologies, and DevOps practices to recommend innovative solutions.

Requirements:

• Experience in Microsoft Azure: Deep understanding of Azure services, including but not limited to Azure Virtual Machines, Azure Container Apps Environment, Azure Machine Learning, Azure Functions, and Azure Cognitive Services.
• Experience in Generative AI: Experience working on full-stack Gen AI solution deployments through rapid-prototyping, MVP to Production grade enterprise solutions, both with Commercial, Open-source models, and Generative AI frameworks such as Lang Chain, LlamaIndex, etc., with a deeper understanding of Global AI regulations, and AI Governance.
• DevOps and CI/CD: Proven experience in DevOps practices, including setting up and managing CI/CD pipelines using GitHub Actions or Azure DevOps.
• Infrastructure as Code: Hands-on experience with IaC tools such as Terraform, ARM templates, or Bicep.
• AI Integration: Experience in integrating AI/ML models into cloud solutions to enhance business processes and outcomes.
• Strong Engineering with Research Mindset: Ability to approach problems with a research-oriented mindset, exploring new technologies and methods to achieve optimal solutions.
• Value-Centric Approach: Ability to balance timelines and deliverables with a strong focus on delivering value-driven solutions.
• Collaborative and Independent: Excellent team player who can collaborate effectively across teams but is also capable of working independently with minimal supervision.

Education, Experience and Soft skills:

• Minimum bachelor's degree (master's degree preferred) in Computer Science, Information Technology, or related fields.
• At least 3+ years of experience in Cloud & AI, with at least 2+ years on Generative AI, and a total of 5+ years of experience in IT.
• Strong problem-solving and critical-thinking skills.
• Excellent communication and interpersonal skills to engage with both technical and non-technical stakeholders.
• Proven ability to manage multiple projects and deliverables simultaneously.
• Willingness to learn and adapt to new technologies and frameworks.