Job Summary

We are seeking an experienced AI Support Expert to oversee the operational support, incident management, and technical maintenance of AI/ML-driven applications built using Python and deployed across AWS and Azure cloud platforms. The ideal candidate will have deep technical expertise in cloud infrastructure, Python-based application development, AI/ML operations (MLOps), and team leadership. This role ensures high availability, reliability, and performance of AI systems that support business-critical processes, spanning across company s Internal and External use cases.

Responsibilities

- Technical Leadership and Team Management: Lead, mentor, and guide a team of support engineers (L1/L2/L3). Foster seamless collaboration with development teams across France and India to ensure smooth handovers and operational readiness. Act as the primary escalation point for complex issues across applications, ML models, and cloud services. Drive continuous improvement initiatives and establish best practices for operational excellence.

- Application Support Troubleshooting: Manage the full lifecycle of issues for AI use cases, serving both internal business units and external clients. Provide end-to-end support for Python-based APIs, microservices, AI/ML pipelines, and data processing systems. Diagnose and resolve issues related to Python environments, dependencies, performance bottlenecks, and integrations. Maintain high availability and optimal performance of production workloads.

- Monitoring, Incident, and AI-Native Operations: Champion the usage of AI-native engineering tools to automate support workflows and improve system observability. Establish monitoring dashboards and alerts through Dynatrace, CloudWatch, Azure Monitor, or Application Insights. Own the full lifecycle of incidents, from detection to root cause analysis and preventive measures. Maintain and ensure adherence to SLA commitments.

Required Qualifications

- Technical Skills: 5-10 years of experience supporting production systems,



preferably AI/ML or data-intensive applications.

- Hands-on experience managing support across various layers: from underlying processes to specific AI use cases and intelligent agents.

- Solid proficiency in Python, debugging, and API frameworks (FastAPI, Flask, Django).

- Experience with AWS (EC2, Lambda, S3, SageMaker, RDS) and Azure (App Services, Functions, Azure ML, Storage, AKS).

- Experience with AI-native engineering tools and automated agentic evaluation frameworks.

- Experience with CI/CD tools (Azure DevOps, GitHub Actions, Jenkins) and infrastructure-as-code.

- Familiarity with containerization (Docker, Kubernetes) and microservices architecture.

Soft Skills

- Global mindset: Ability to work effectively in a multicultural environment, specifically collaborating with teams in Europe and Asia.

- Excellent problem-solving skills and ability to handle high-pressure incidents.

- Strong leadership, mentoring, and team management capabilities.

- Effective communication and stakeholder management skills.

Preferred Qualifications

- Certifications such as AWS and Azure Administrator, or Azure/AWS Data/AI certifications.

- Experience with MLOps tools (MLflow, Kubeflow, Sagemaker Pipelines, Azure ML Pipelines).

- Knowledge of DevSecOps, automation, and cost optimization best practices.

- Experience in ITIL practices for incident, problem, and change management.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

Role: Search Engineer,

Industry Type: Electrical Equipment,

Department: Engineering - Software & QA,

Employment Type: Full Time, Permanent

Role Category: Software Development

Education

UG: Any Graduate

PG: Any Postgraduate read more

Key Skills aiai engineeraksapisapp servicesapplication developmentapplication insightsapplication supportarchitectureautomationawsazureazure cloudazure devopsazure mlcd toolschange managementcloudcloud infrastructure

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