AI SRE Engineer

EDGE Executive Search; Bengaluru; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

EDGE Executive Search is seeking an AI PrSRE Engineer to support and operate regulated banking AI/ML solutions. The role emphasizes high availability, resilience, and risk management of AI systems that power essential banking services.

You will work with Data Science, Engineering, Risk, and Compliance teams to ensure secure deployment, monitoring, and compliance across AI workloads in a regulated environment.

Qualifications

• Experience in production support / SRE / platform engineering, preferably in banking or financial services.
• Strong understanding of AI/ML lifecycle and model operations (MLOps).
• Experience with cloud platforms (Azure preferred in banking), including secure workloads.
• Proficiency in Python and scripting for debugging and automation.
• Hands-on experience with Docker, Kubernetes, and microservices architectures.
• Familiarity with MLOps tools (MLflow, Azure ML, SageMaker, etc.).
• Experience with monitoring & observability tools (CloudWatch, Splunk, Grafana, Prometheus).
• Knowledge of data pipelines, APIs, batch and real-time processing systems.
• Experience with incident management tools (e.g., ServiceNow).
• Understanding of model risk management (MRM) and audit expectations.
• Awareness of data governance, lineage, and controls.
• Familiarity with security standards and IAM.

Responsibilities

• Provide L2/L3 production support for AI/ML models and data pipelines used in banking systems.
• Monitor model performance, drift, data quality, and operational health of AI services.
• Ensure stability and uptime of AI platforms supporting customer-facing and regulatory workloads.
• Perform incident management, RCA, and problem management in line with ITIL practices.
• Collaborate with Data Science, Engineering, Risk, and Compliance teams.
• Support secure deployment, release, and rollback of models in production.
• Implement monitoring, alerting, and audit logging to meet regulatory and audit requirements.
• Ensure adherence to data privacy, governance, and financial regulatory standards (e.g., GDPR, model risk frameworks).
• Support disaster recovery (DR) and business continuity (BCP) plans for AI workloads.
• Identify opportunities for automation, operational efficiency, and cost optimization.

Skills

SRE / platform engineering

AI/ML lifecycle awareness

Incident management

Cross-team collaboration

Security & governance mindset

Education

Bachelor's degree in CS/IS or related field

Tools

Azure

Docker

Kubernetes

MLflow

Azure ML

SageMaker

CloudWatch

Splunk

Grafana

Prometheus

ServiceNow

IAM/Security controls

Job description

The Job

We are looking for an AI PrSRE Engineer to support and operate AI/ML solutions within a regulated banking environment. The role focuses on ensuring high availability, resilience, compliance, and risk management of AI systems that support critical banking services.

Responsibilities

• Provide L2/L3 production support for AI/ML models and data pipelines used in banking systems
• Monitor model performance, drift, data quality, and operational health of AI services
• Ensure stability and uptime of AI platforms supporting customer-facing and regulatory workloads
• Perform incident management, root cause analysis (RCA), and problem management in line with ITIL practices
• Collaborate with Data Science, Engineering, Risk, and Compliance teams
• Support secure deployment, release, and rollback of models in production
• Implement monitoring, alerting, and audit logging to meet regulatory and audit requirements
• Ensure adherence to data privacy, governance, and financial regulatory standards (e.g., GDPR, model risk frameworks)
• Support disaster recovery (DR) and business continuity (BCP) plans for AI workloads
• Identify opportunities for automation, operational efficiency, and cost optimization

Your Profile

Requirements

• Experience in production support / SRE / platform engineering, preferably in banking or financial services
• Strong understanding of AI/ML lifecycle and model operations (MLOps)
• Experience with cloud platforms (Azure preferred in banking), including secure workloads
• Proficiency in Python and scripting for debugging and automation
• Hands-on experience with Docker, Kubernetes, and microservices architectures
• Familiarity with MLOps tools (MLflow, Azure ML, SageMaker, etc.)
• Experience with monitoring & observability tools (CloudWatch, Splunk, Grafana, Prometheus)
• Knowledge of data pipelines, APIs, batch and real-time processing systems
• Experience with incident management tools (e.g., ServiceNow)
• Understanding of model risk management (MRM) and audit expectations
• Awareness of data governance, lineage, and controls
• Familiarity with security standards and identity access management (IAM)
• Nice to have
• Exposure to AI governance frameworks and explainability tools
• Experience with fraud detection, credit risk, or financial analytics models
• Knowledge of secure DevOps (DevSecOps) practices
• Relevant certifications (AWS, MLOps)