Senior Technical Lead

• *Job Summary**
• --------------

• *Expert, AI Application Sustenance – Engineer**

We are seeking an experienced **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.

• *Key Responsibilities**
• -----------------------

• *1\. Technical Leadership \& Team Management**

• Lead, mentor, and guide a team of support engineers (L1/L2/L3\).
• 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.

• *2\. Application Support \& Troubleshooting**

• 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.

• *3\. Monitoring, Incident, and Problem Management**

• 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.

• *Skill Requirements**
• ---------------------

• *Technical Skills**

• 5–10 years of experience supporting production systems, preferably AI/ML or data\-intensive applications.
• Strong 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 CI/CD tools (Azure DevOps, GitHub Actions, Jenkins) and infrastructure\-as\-code.
• Familiarity with containerization (Docker, Kubernetes) and microservices architecture.
• Strong understanding of AI/ML concepts, model deployment and monitoring.

• *Must Have Skill**
• ------------------

AI/ML Tools \- Others,Amazon Sagemaker,Flask,Microservices,MLOps (Machine Learning Operations),Python

• *Good to Have Skill**
• ---------------------

• *Other Requirements**
• ---------------------

• 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.