Sourcebae
Website:
sourcebae.com
Company:
https://www.linkedin.com/company/sourcebae
Seniority: Mid-Senior level
Industries: Technology, Information and Internet
Job details:
AI Production SRE
Position: AI Production SRE
Experience: 8+ Years
Location: Bangalore
Job Type: Fulltime - Remote / Hybrid
Budget: 35 LPA
Role Overview
We are looking for an AI Production Support 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.
Key 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 AI/ML 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.
Required Skills & Experience
Cloud & AI Platforms
AWS SageMaker
Amazon EC2
Amazon EKS (Elastic Kubernetes Service)
AWS Lambda
Amazon S3
Amazon CloudWatch
MLOps & Model Management
SageMaker Pipelines
MLflow
Model Registry
Model Deployment Frameworks
Containerization & Orchestration
Docker
Kubernetes (EKS)
Monitoring & Observability
AWS CloudWatch
AWS CloudTrail
Prometheus
Grafana
OpenTelemetry
CI/CD & DevOps
AWS CodePipeline
AWS CodeBuild
AWS CodeDeploy
Jenkins
GitHub Actions
Data & Integration
AWS Glue
Amazon Kinesis
Amazon EventBridge
REST APIs
SQL / NoSQL (Amazon RDS, DynamoDB)
Security & Identity
IAM
AWS KMS
AWS Secrets Manager
VPC Security (Subnets, NACLs, Security Groups)
Resilience & Backup
AWS Backup
Cross-Region Replication
Disaster Recovery (Multi-AZ / Multi-Region)
Additional Requirements
Experience in Production Support, SRE, or Platform Engineering, preferably in Banking or Financial Services.
Strong understanding of the AI/ML lifecycle and 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 architecture.
Familiarity with MLOps tools such as MLflow, Azure ML, or SageMaker.
Experience with monitoring and observability tools including CloudWatch, Splunk, Grafana, and Prometheus.
Knowledge of data pipelines, APIs, batch, and real-time processing systems.
Experience with incident management tools such as 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 DevSecOps practices.
AWS and MLOps certifications.
Click on Apply to know more.
