SR-45859 - AI Support Expert

Experience: 5–10 Years

- CTC:
- 5–7 Years: Up to 30 LPA (Flexible)
- 7–10 Years: Up to 36 LPA (Flexible)

- Notice Period: Immediate Joiners
- Location: Bangalore (Client Location)
- Work Mode: 3 Days/Week (WFO)/Hybrid

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Core skills

SRE/DevOps (cloud infra, CI/CD, containers)

L3 Application Support (Python, APIs, production incidents)

AI-adjacent Operations (supporting ML pipelines, not owning them)

Title: AI Support expert

Location: Bengaluru (Work from client location 3 days in a week)

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.

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.

Key Responsibilities

1. Technical Leadership & 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.

2. 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.

3. 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.
- 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 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.
- Robust 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.

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