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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) .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.