Project Role : Operations Engineer

Project Role Description : Support the operations and/or manage delivery for production systems and services based on operational requirements and service agreement.

Must have skills : AWS Administration

Good to have skills : NA
Minimum 7.5 year(s) of experience is required

Educational Qualification : 15 years full time education

Summary:
A Principal Engineer - Cloud leads the hands-on design, build, and operation of large-scale cloud infrastructure across AWS and GCP. The role is accountable for engineering secure, resilient, and cost-optimized cloud platforms - building real infrastructure, writing real code, and owning outcomes end to end alongside product, security, and application engineering teams.

This individual operates as a recognized cloud engineering authority - setting platform standards, driving infrastructure automation, and solving complex distributed cloud Infrastructure challenges including having good understanding of the insurance industry. In a financial services context, engineering decisions must satisfy stringent regulatory requirements including PCI DSS, SOX, and DORA, alongside enterprise-grade reliability and availability commitments.

Roles Responsibilities:
Cloud Platform Engineering
- Design, build, and operate large-scale, cloud-native infrastructure across AWS and GCP - owning platform reliability, security posture, and cost efficiency
- Implement and maintain infrastructure-as-code across both cloud platforms using Terraform and native tooling - enforcing standards, modularity, and drift detection
- Build and maintain CI/CD pipelines, GitOps workflows, and deployment automation for cloud infrastructure and platform services
- Engineer landing zones, account vending, and governance guardrails on AWS (Control Tower, SCPs) and GCP (Resource Manager, Org Policies)
AI Orchestration: High Level understanding of LangChain, LlamaIndex, CrewAI - agentic workflow design, multi-agent orchestration, tool calling, human-in-the-loop workflows
- Design and implement cloud networking - AWS VPC, Transit Gateway, Direct Connect and GCP VPC, Shared VPC, Cloud Interconnect - for hybrid and multi-cloud connectivity
- Implement security controls across IAM, network policy, encryption, secrets management, and audit logging on both platforms
- Drive platform observability - metrics, logging, distributed tracing, and alerting using CloudWatch, GCP Operations Suite, and third-party tooling
- Perform capacity planning, cost analysis, and right-sizing to maintain efficient cloud spend across AWS and GCP estates
LLM AI Tooling: High Level Understanding of OpenAI, Anthropic Claude, Google Gemini - prompt engineering, RAG architecture, vector databases (Pinecone, Weaviate, ChromaDB), LLMOps




Application Container Platform Engineering
- Engineer and operate Kubernetes-based container platforms - EKS on AWS and GKE on GCP - including cluster lifecycle, node management, networking, and security hardening
- Define and enforce standards for microservices, APIs, event-driven architectures, and data platform integrations across cloud environments
- Collaborate with application engineering teams on cloud-native design patterns - serverless, service mesh, and distributed data stores - Build and maintain developer platform tooling - internal developer portals, self-service infrastructure, and platform APIs - to accelerate engineering delivery
- Drive observability and reliability engineering practices - SLIs, SLOs, error budgets, and chaos engineering - across cloud-hosted services
- Support secure software delivery - SAST, DAST, container image scanning, and supply chain security in CI/CD pipelines
Technical Leadership Engineering Excellence
- Set cloud engineering standards, patterns, and reference architectures - codified in reusable Terraform modules, runbooks, and design guides
- Lead proof-of-concept and spike work for emerging cloud technologies - making build-vs-buy recommendations grounded in engineering evidence
- Conduct technical design reviews and production readiness assessments for cloud-hosted services
- Mentor senior and mid-level engineers - providing hands-on guidance on IaC, cloud-native patterns, and production operations
- Drive continuous improvement of the cloud platform - reducing toil through automation, improving reliability, and eliminating technical debt
- Contribute engineering patterns and reusable modules back to internal platform teams and cloud centre of excellence

Professional Technical Skills:
Must-Have Technical Skills
Infrastructure as Code: Terraform (advanced) - modular design, remote state, workspace strategy, and policy-as-code (Sentinel/OPA) across AWS and GCP
Containers Kubernetes: EKS and GKE - cluster lifecycle, CNI, RBAC, admission controllers, network policies, and production-grade operations
Cloud Networking: Deep expertise in hybrid connectivity, multi-cloud routing, DNS strategy, and network security across both platforms
Security Engineering: IAM design, zero-trust principles, encryption at rest/in transit, secrets management (Vault, AWS Secrets Manager, GCP Secret Manager), and CSPM
CI/CD Automation:



GitHub Actions, ArgoCD, Terraform Cloud, or equivalent - GitOps workflows, pipeline security, and infrastructure deployment automation
AI Orchestration: High Level Understanding of LangChain, LlamaIndex, CrewAI - agentic workflow design, multi-agent orchestration, tool calling, human-in-the-loop workflows
Observability: Metrics, logging, and distributed tracing at scale - SLO engineering, alerting design, and incident response tooling
Scripting Development: Python or Go - automation scripting, SDK usage for AWS and GCP, and platform tooling development
LLM AI Tooling: High Level understanding of OpenAI, Anthropic Claude, Google Gemini - prompt engineering, RAG architecture, vector databases (Pinecone, Weaviate, ChromaDB), LLMOps
Incident Management: Production incident ownership, structured RCA, and reliability engineering practices in high-availability FSI environments
Cost Engineering: FinOps practices - reserved instance/committed use optimisation, tagging strategy, and cost allocation across AWS and GCP estates
Preferred / Advantageous
- Experience with service mesh (Istio or Linkerd) for microservices networking and observability
- Familiarity with data platform engineering - Kafka, Spark, or cloud-native analytics services on AWS or GCP
- Exposure to FinOps tooling - CloudHealth, Apptio Cloudability, or native cloud cost management platforms
- Background in platform engineering, SRE, or cloud infrastructure consulting within financial services

Certifications

- AWS Solutions Architect
- Professional GCP Professional Cloud Architect AWS DevOps Engineer
- Skilled or GCP DevOps Engineer

- Cloud platforms on AWS and GCP are secure, observable, and reliably operated - meeting FSI SLA and regulatory requirements consistently
- Infrastructure-as-code coverage is comprehensive - environments are reproducible, drift-free, and deployable through automated pipelines without manual intervention
- Engineering teams across the organisation adopt platform standards, reusable modules, and cloud-native patterns - reducing bespoke build effort and improving consistency - Platform reliability improves measurably quarter-on-quarter - MTTR reduces, toil decreases, and error budgets are maintained across cloud-hosted services
- Cross-functional stakeholders - security, application, data, and operations teams - regard the Principal Engineer as a technically authoritative, delivery-focused partner who unblocks rather than bottlenecks

- The candidate should have minimum 12 years of experience in Amazon Web Services (AWS).

- This position is based at our Bengaluru office.

- A 15 years full time education is required.

Qualification 15 years full time education

📌 Operations Engineer (Bengaluru)
🏢 Accenture
📍 Bengaluru