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.

Experience
5-9 yrs