Staff Engineer, Cloud Engineering

About Us

Automation Anywhere is the leader in Agentic Process Automation (APA) transforming how work gets done with AI-powered automation. Its APA system built on the industrys first Process Reasoning Engine (PRE) and specialized AI agents combines process discovery RPA end-to-end orchestration document processing and analyticsall delivered with enterprise-grade security and governance. Guided by its vision to fuel the future of work Automation Anywhere helps organizations worldwide boost productivity accelerate growth and unleash human potential.

Our Opportunity:

We are seeking a highly skilled Multi-Cloud FinOps Staff Engineer to contribute to cloud financial optimization AI/GenAI cost governance Kubernetes workload efficiency MLOps optimization and enterprise chargeback/show back strategy across Azure AWS and GCP environments.

This role combines:

Cloud architecture

FinOps governance

AI/ML platform optimization

Data engineering

Financial analytics

Enterprise budgeting & forecasting

The ideal candidate will drive cloud profitability tenant-level usage accountability and intelligent cost optimization for modern AI-powered platforms.

Location:

• Bangalore

Who Youll Report To:

• Director Cloud Engineering

You Will Make an Impact By Being Responsible For:

Technical Advisory

Conduct deep-dive architectural reviews of high-spend services to identify inefficiencies.

Provide specific code-level and infrastructure recommendations such as refactoring for serverless right-sizing containerized environments and optimizing storage tiering logic.

Advise engineering teams on cost-efficient design patterns during the initial design phase to prevent technical debt in the cloud bill.

Translate high-level savings targets into actionable technical backlogs.

Oversee and develop scripts (e.g. Python Bash) and Infrastructure as Code (Terraform) for automated governance.

Build and maintain technical guardrails that prevent cost leaks before they occur.

Automate the detection and remediation of orphaned resources unoptimized snapshots or inefficient architectural patterns.

Translate complex technical optimization successes into business value metrics for Senior Leadership.

Provide technical feasibility assessments for long-term cloud financial commitments and strategic procurement decisions.

Financial Planning Reporting Budgeting & Forecasting

Build cloud financial forecasting models

Drive: Budget planning Forecast variance analysis Margin optimization Cost anomaly detection Capacity planning

Develop KPI frameworks for: Cost per tenant Cost per transaction Cost per AI request Cost per model training run Gross margin tracking

Partner with Finance and Engineering teams for monthly business reviews

Build executive FinOps dashboards and reporting systems

Present optimization opportunities to leadership

Establish cloud governance standards and compliance controls

Enable data-driven decision making through financial analytics

Kubernetes & Container Cost Optimization

Lead Kubernetes FinOps initiatives for enterprise-scale clusters

Optimize: Node utilization Autoscaling policies Spot/preemptible workloads Namespace-level cost visibility GPU allocation Multi-tenant clusters

Implement workload rightsizing strategies using: CPU/memory profiling Idle resource detection Bin-packing optimization Scheduling efficiency.

Build tenant-level Kubernetes cost attribution and dashboards

Tools Exposure: Kubecost OpenCost Prometheus/Grafana AKS/EKS/GKE Karpenter Cluster Autoscaler

GenAI & Azure OpenAI Cost Optimization

Optimize: Token consumption Prompt engineering efficiency Model selection strategies Context window utilization Embedding/vector database cost

Implement: AI governance AI usage metering AI quota management Cost guardrails Token forecasting models

Analyze AI workload ROI and business value realization

Preferred knowledge:

Azure OpenAI Service Vector DBs RAG GPU optimization AI inferencing economics

Tenant-Level Usage Tracking & Chargeback

Design tenant-level metering systems for: API usage AI token consumption Kubernetes namespaces GPU consumption Storage utilization Data pipeline execution

Build: Showback dashboards Chargeback engines Department-level cost transparency

Ensure accurate tagging allocation and reconciliation mechanisms

Data/Feature Engineering & Pipeline Optimization

Architect scalable and cost-optimized data pipelines

Optimize: ETL/ELT workloads Streaming pipelines Data lake storage tiers Data retention policies Query optimization

Implement data observability and cost intelligence frameworks

prefered knowledge : Databricks BigQuery

You Will Be a Great Fit If You Have:

Bachelors or Masters degree in Computer Science Data Engineering or related field

6 years of experience in Cloud engineering FinOps or DevOps roles

3 years in FinOps or cloud financial governance

Deep understanding of cloud billing models pricing structures and cost optimization strategies

Hands-on experience with AWS Cost Explorer Azure Cost Management GCP Billing and FinOps tools like CloudHealth etc.

Strong analytical skills with proficiency in Data & Visualization: SQL Python Power BI / Tableau / Grafana Cost analytics dashboards (cloudhealth Aptio cloudzero)

FinOps Certified Practitioner or similar certification is a plus

End-to-end understanding ofhow cloud-basedweb applicationswork and their architecture

Experience with Docker andKubernetesin production

Experience with automation tools like Terraform or Ansible

Exposure to AI platform economics

Ready to Revolutionize Work

This is an opportunity to work with a global passionate team pioneering technology thats redefining the way people work everywhere. Join us and discover the many ways that you can have an impact achieve your potential and go be great.