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34129BR Bangalore - Global Axis Job Description Job Description: Senior Cloud & AI Engineer Role Overview We are seeking a highly skilled Senior Cloud & AI Engineer to design, build, and optimize cloud-based AI/ML platforms. You will drive the platformization of our cloud infrastructure, leveraging Azure, OpenAI, and MLOps to deploy scalable AI solutions. This role is critical for advancing our AI capabilities and enabling seamless integration of tools like Copilot to enhance productivity and innovation. Exposure to AI Foundry preferred. Key Responsibilities Cloud Platform Development: Architect, implement, and manage Azure-based cloud platforms to support AI/ML workloads at scale. AI/ML Solutions: Design and deploy generative AI models (OpenAI) and end-to-end ML pipelines, ensuring robust MLOps practices for monitoring, testing, and CI/CD. Copilot Integration: Develop and optimize Copilot-based tools to automate code generation, data analysis, and workflow efficiency. Automation & Optimization: Script infrastructure-as-code (IaC) using Python, automate cloud resource management, and enhance platform reliability. Cross-functional Collaboration: Partner with data scientists and developers to operationalize AI models and ensure alignment with business goals. Best Practices: Establish governance, security, and cost-optimization strategies for cloud and AI resources. Required Skills & Qualifications Cloud Expertise: 5+ years in cloud engineering with Azure (IaaS/PaaS, AKS, Databricks, Synapse) and a focus on cloud platformization. AI/ML Proficiency: Hands-on experience with OpenAI, generative AI, and AI/ML Ops (e.g., MLflow, Azure ML). Programming: Advanced Python skills for automation, API development, and scripting. Copilot Tools: Proven ability to implement Copilot (GitHub/GitLab Copilot, Azure Copilot) for code/process automation. DevOps: Experience with CI/CD (Azure DevOps), containerization (Docker/Kubernetes), and IaC (Terraform/Bicep). Analytical Skills: Ability to troubleshoot complex systems and optimize performance. Preferred Qualifications Azure certifications (e.g., Azure Solutions Architect, Azure AI Engineer). Familiarity with big data tools (Spark, Delta Lake) and LLM fine-tuning. Knowledge of other cloud platforms (AWS/GCP) or AI frameworks (LangChain, Hugging Face). Education Bachelor’s/Master’s in Computer Science, Engineering, or related field. Qualifications B.Tech Range of Year Experience-Min Year 7 Range of Year Experience-Max Year 15 Show more Show less
