Senior Cloud & ML Infrastructure Engineer

Amura’s Vision 

We believe that the most under-appreciated route to releasing untapped human potential is to build a healthier body, and through which a better brain. This allows us to do more of everything that is important to each one of us.

Billions of healthier brains, sitting in healthier bodies, can take up more complex problems that defy solutions today, including many existential threats, and solve them in just a few decades.

Billions of healthier brains will make the world richer beyond what we can imagine today. The surplus wealth, combined with better human capabilities, will lead us to a new renaissance, giving us a richer and more beautiful culture.

These healthier brains will be equipped with deeper intellect, be less acrimonious, more magnanimous, and have a kinder outlook on the world, resulting in a world that is better than any previous time.

We find this vision of the future exhilarating. Our hopes and dreams are to create this future as quickly as possible and ensure that it is widely distributed and optimized to maximize all forms of human excellence. 

Role Overview 

We are looking for a highly skilled Senior DevOps Engineer (AI-Native Infrastructure & Platform Engineering) with deep expertise in AWS cloud infrastructure, automation, AI infrastructure operations, and modern DevOps/SRE practices.

This role goes beyond traditional DevOps and requires a seasoned specialist capable of building and operating AI-ready infrastructure platforms that support high-throughput APIs, LLM/AI workloads, GPU-based compute, data-intensive systems, real-time inference pipelines, and scalable ML platforms.

You will be responsible for architecting, automating, securing, and optimizing highly scalable and cost-efficient cloud environments that enable high-velocity engineering and AI teams. This is an ideal position for someone who combines technical ownership, an automation-first mindset, and a passion for developer productivity and platform reliability. 

Key Responsibilities 

Cloud Infrastructure & Platform Engineering (AWS) 

• Architect, deploy, and manage highly scalable and secure infrastructure on AWS. Design cloud platforms supporting AI/ML workloads, data pipelines, real-time APIs, and high-concurrency backend systems.
• Hands-on expertise with key AWS services including EC2, ECS/EKS, Lambda, RDS, DynamoDB, S3, VPC, CloudFront, IAM, CloudWatch, and GPU-enabled instances.
• Build and maintain Infrastructure-as-Code (IaC) using Terraform, CloudFormation, or AWS CDK.
• Design multi-AZ and multi-region architectures for high availability and disaster recovery (HA/DR).
• Build reusable platform templates and shared infrastructure modules. 

AI/ML Infrastructure & MLOps 

• Build and maintain infrastructure for LLM applications, AI inference workloads, model serving platforms, vector databases, and feature stores.
• Support GPU-based workloads and optimize compute/storage usage.
• Enable scalable deployment patterns for AI applications using Kubernetes/EKS. Collaborate with Data Science and ML Engineering teams on model deployment, training/tuning of models, CI/CD for ML systems, experiment environments, and reproducibility.
• Support orchestration and deployment of AI workflows and inference services while implementing observability and reliability for AI pipelines. 

CI/CD, Automation & Developer Productivity 

• Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline.
• Automate deployments, environment provisioning, and release workflows.
• Build self-service developer platforms, preview environments, and reusable deployment workflows to improve developer productivity.
• Implement automated patching, scaling, backups, cleanup workflows, and drift detection. 

Containers, Kubernetes & Platform Reliability

• Manage Docker-based environments, containerized applications, and optimize workloads using Kubernetes (EKS) or ECS/Fargate.
• Manage autoscaling, cluster health, node pools, ingress, service mesh, and workload isolation.
• Optimize infrastructure for performance, resilience, and cost-efficiency.
• Implement progressive deployment strategies including blue/green, canary, and rolling deployments. 

Observability, Incident Response & SRE Practices

• Implement observability stacks using CloudWatch, Prometheus, Grafana, ELK, Datadog, OpenTelemetry, or New Relic.
• Build actionable dashboards and intelligent alerting systems while defining and tracking SLIs, SLOs, and SLAs.
• Lead incident response, root cause analysis, and blameless postmortems to reduce operational toil and improve MTTR.

FinOps, Cost Governance & Security

• Continuously monitor and optimize cloud costs (compute utilization, storage lifecycle, GPU usage, and data transfer) using AWS Cost Explorer, Budgets, Trusted Advisor, CloudHealth, or Kubecost.
• Implement AWS security best practices for IAM, VPCs, security groups, NACLs, encryption, and manage secrets using KMS, SSM Parameter Store, or Vault.
• Build secure CI/CD pipelines with automated security checks, least-privilege access, audit logging, and ensure compliance readiness for ISO 27001, SOC2, and GDPR.

Collaboration, Leadership & Platform Culture

• Work closely with engineering, AI/ML, QA, product, and operations teams to drive a DevOps, SRE, GitOps, and automation-first culture.
• Mentor junior DevOps and Platform Engineers while creating and maintaining detailed runbooks, architecture diagrams, and platform documentation.

Skills & Qualifications

Must-Have:

• 7+ years of experience in DevOps, SRE, Platform Engineering, or Cloud Infrastructure Engineering.
• Strong expertise in AWS cloud architecture, services, and deep understanding of Kubernetes (EKS), containers, and cloud-native systems.
• Strong Infrastructure-as-Code expertise using Terraform, CloudFormation, or CDK. Strong Linux administration, networking, DNS, routing, and load balancing knowledge. Strong scripting/programming experience in Python, Bash, or Go (preferred). Experience with CI/CD automation, GitOps workflows, and observability platforms supporting scalable production systems.

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Here are answers to some questions you may have

Where is your office?

Chennai (Velachery)

Work Model

Work from Office – because great stories are built in person!

Do you have an online presence?

https://amura.ai (we are @AmuraHealth on all social media)

Job Description: Lead - Cloud Engineering (AWS / Azure)

Role Title: Lead - Cloud Engineering

Experience Level: 10+ Years

Domain Focus: Healthcare AI & Cloud Infrastructure

Location: Remote

Job Overview

We are seeking an experienced Lead - Cloud Engineering with over 10 years of IT experience to lead our cloud strategy, architecture, and infrastructure teams. In this role, you will oversee end-to-end cloud deployment, multi-cloud migration, and scalable architecture designed to support cutting-edge Generative AI applications in the healthcare technology domain.

The ideal candidate brings deep technical expertise in both AWS and Azure, strong hands-on capability in cloud infrastructure, and proven leadership experience driving security, compliance, and team growth.

Key Responsibilities

Cloud Architecture & Migration

• Lead the architecture, design, and execution of cloud migrations, deployments, and modernizations across AWS and Azure environments.
• Drive Infrastructure as Code (IaC) standards using Terraform, CloudFormation, or Bicep to ensure scalable, automated infrastructure provisioning.
• Build high-availability, low-latency architectures optimized for data-intensive Generative AI and Machine Learning workloads.

Security & Healthcare Compliance

• Enforce healthcare security standards including HIPAA, HITRUST, SOC 2, and data governance best practices across all cloud assets.
• Implement Zero-Trust security, Identity Access Management (IAM), data encryption key management, and continuous vulnerability monitoring.

Leadership & Team Management

• Manage, mentor, and scale a high-performing team of DevOps, Cloud, and SRE Engineers.
• Drive Agile workflows, sprint planning, incident response frameworks, and SLA compliance.
• Collaborate closely with Data Engineering, AI/ML, and Software Product teams to align infrastructure with business roadmaps.

Operations & FinOps

• Establish cloud cost optimization strategies (FinOps) to manage computing costs associated with AI models and large-scale data processing.
• Manage monitoring, alerting, and telemetry frameworks (e.g., Prometheus, Datadog, CloudWatch) to ensure 99.99% uptime.

Key Requirements

• Experience: 10+ years of overall IT experience with at least 5+ years in a cloud leadership or lead architect role.
• Cloud Platforms: Advanced hands-on expertise with both AWS (e.g., EC2, S3, EKS, Bedrock, SageMaker) and Azure (e.g., AKS, Azure OpenAI, Blob, Virtual Machines).
• DevOps & IaC: Strong background in Terraform, Docker, Kubernetes, CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins).
• Domain Knowledge: Prior experience building or managing cloud environments within Healthcare, Life Sciences, or HealthTech is strongly preferred.
• AI/ML Familiarity: Experience supporting cloud infrastructure for machine learning pipelines, LLM deployments, or GPU compute management.
• Certifications (Preferred): AWS Certified Solutions Architect – Professional, Azure Solutions Architect Expert, or Certified Kubernetes Administrator (CKA).

We are looking for a hands-on Senior AWS Cloud Engineer to lead the infrastructure build, optimization, automation, and production deployment of a Multi-Agent AI Chatbot Platform hosted on AWS. The development environment is already in place, and the successful candidate will drive the solution through testing, integrations, and production go-live.

Key Responsibilities

• Review, validate, and optimize existing Terraform code and AWS infrastructure.
• Establish and manage integrations with enterprise platforms such as ServiceNow, Workday, and other third-party systems.
• Design, build, and support secure, scalable, and highly available AWS environments.
• Implement and automate CI/CD pipelines and Infrastructure-as-Code practices.
• Lead infrastructure testing, performance tuning, and production readiness activities.
• Drive deployment and operationalization of the platform in the Production environment.
• Implement cloud governance, security, monitoring, and FinOps best practices.
• Troubleshoot and resolve complex cloud infrastructure issues.

Required Skills & Experience

• 10+ years of IT experience with strong expertise in AWS Cloud Engineering.
• Proven experience designing, deploying, and managing AWS production environments.
• Strong hands-on experience with Terraform and Infrastructure-as-Code.
• Experience with CI/CD pipeline automation and DevOps practices.
• Expertise in AWS services including VPC, IAM, EC2, S3, Lambda, CloudWatch, and networking.
• Experience in performance optimization, reliability, and cloud cost management (FinOps).
• Strong scripting and automation skills.
• Experience integrating enterprise applications through APIs and secure connectivity patterns.

 The Role 

As a **DevOps Engineer** you'll own the infrastructure and delivery backbone that 

keeps our platform running as we grow. You'll build the CI/CD, cloud infrastructure, and 

observability that let a small, fast-moving team ship confidently — and you'll keep our AI and 

data workloads reliable and affordable at scale. 

This is a hands-on role with real ownership: you won't be maintaining someone else's setup, 

you'll be shaping ours. You'll work closely with the backend, AI/ML, and data teams to make 

deployment boring, incidents rare, and scaling a non-event. --- 

What You'll Own 

**CI/CD & developer experience** 

- Build and maintain fast, reliable CI/CD pipelines so engineers ship multiple times a day with 

confidence. - Make the path from commit to production simple, safe, and repeatable, with sensible 

automated testing, rollbacks, and release controls. 

**Cloud infrastructure & IaC** - Own our cloud infrastructure (AWS/GCP) end to end, managed as code (Terraform or 

similar) — no click-ops. - Design for scale and cost-efficiency as store and conversation volumes grow. 

**Containers & orchestration** - Run our services on containers/Kubernetes: deployments, autoscaling, networking, and 

resource management. - Support the specific needs of AI/ML workloads, including GPU-backed inference and batch 

processing for the speech pipeline. 

**Reliability & observability (SRE)** - Own uptime, performance, and incident response — monitoring, logging, tracing, alerting, 

on-call, and blameless postmortems. - Define and defend SLOs; keep the platform dependable as it scales across clients. 

**Data & pipeline infrastructure** - Support the infrastructure behind large-scale, edge-to-cloud data movement and 

processing (audio ingestion, ASR/AI pipelines, analytics). - Keep data workloads reliable, performant, and cost-aware. 

**Security & compliance** - Bake security into the platform: secrets management, IAM/least-privilege, encryption in 

transit and at rest, network hardening, and vulnerability management. - Support compliance readiness (including India's DPDP Act and enterprise-client security 

requirements) for a product that handles sensitive customer conversations. 

**Cost & scale** - Own cloud cost visibility and optimization; make scaling decisions that balance reliability 

and spend. --- 

What You'll Bring - 6+ years in DevOps, SRE, platform, or infrastructure engineering, running production 

systems at meaningful scale. - Strong hands-on experience with a major cloud provider (**AWS or Azure or GCP**) and 

Infrastructure-as-Code (**Terraform** or equivalent). - Solid experience with **containers and Kubernetes** in production. - Experience building and owning **CI/CD** pipelines (e.g. GitHub Actions, GitLab CI, 

Jenkins, Argo, or similar). 

- Comfort with a scripting/automation language (Python, Go, or Bash) and a strong 

automation-first mindset. - Real experience with **observability** (Prometheus/Grafana, ELK, Datadog, 

OpenTelemetry, or similar) and running incident response / on-call. - A security-conscious approach — secrets, IAM, encryption, and least-privilege as defaults. - Startup temperament: ownership, pragmatism, and a bias to automate and ship. - Based in or willing to relocate to Bangalore, and up for an onsite/hybrid, in-person team. 

Bonus Points - Experience running **ML/AI or GPU workloads** in production (inference serving, batch 

pipelines, model deployment). - Experience with data-intensive infrastructure — streaming/queues (Kafka, SQS), data 

pipelines, or large object/audio storage. - Exposure to **edge devices / IoT fleets**, OTA updates, or high-volume device-to-cloud 

ingestion. - Experience with compliance/security frameworks (SOC 2, ISO 27001, DPDP). - FinOps / cloud cost-optimization experience. - Early-stage startup experience. --- 

Why Join - Own infrastructure that's already live with leading retail brands and growing fast — real 

scale, real impact. - Work across genuinely interesting workloads: speech AI, GPU inference, large-scale data, 

and edge-to-cloud ingestion. - Small team, high ownership, direct line to engineering leadership — your decisions ship. - Build the platform foundation of a category-defining product from an

About Shopalyst:

Shopalyst offers a Discovery Commerce platform for digital marketers. Combining data, AI and deep integrations with digital media and e-commerce platforms, Shopalyst connects people with products they love. More than 500 marquee brands leverage our SaaS platform for data driven marketing and sales in 30 countries across Asia, Europe and Americas. We have offices in Fremont CA, Bangalore, and Trivandrum. Our company is backed by Kalaari Capital.

About the Role:

• This position is responsible for end to end management of Shopalyst's cloud infrastructure platform (AWS and Google Cloud).
• Candidate should have a bachelor's degree in Computer Science and Engineering (or equivalent) plus minimum 3+ years of experience in managing AWS cloud infrastructure.

Core responsibilities:

Infra management

• Review infrastructure change requests, suggest & implement optimal solution in terms of performance, maintainability & cost
• Keep the infrastructure updated/upgraded. This includes servers, operating system, packages and application software
• Maintain all infrastructure configuration as IaC (Infrastructure as Code)

Infra monitoring and site reliability

• Continuous monitoring of infrastructure and ensuring 24x7 availability
• Implement/maintain automated alerting mechanisms for handling infra outages
• Document and maintain infra recovery procedures, ensure successful backup of critical data
• Continuously monitor infra utilization and alert on when to scale up/scale down instances

Infra Security, Compliance & Certifications

• Infrastructure access management - ensure least privilege as the default policy. Review infra access periodically. Manage access to critical systems like AWS/Open VPN
• Adherence to CIS/AWS security benchmarks on AWS Security Hub
• Implement controls required for different attestations/certifications like SOC 2 Type 2,ISO 27xxx, PCI DSS etc

DevOps

• Enable CI/CD process for application deployment

Infra cost monitoring and optimisation

• Services-wise infrastructure cost monitoring analysis and optimisation

Infra trends and new services

• Evaluate new cloud services, analyse feasibility of adoption

Required Skills and Experience:

• AWS: 3+ years experience with using a broad range of AWS technologies (e.g. EC2,S3, ELB, VPC,Route 53, IAM, CloudWatch, CloudFront, RDS, Lambda, Glacier) to develop and maintain an Amazon AWS based cloud solution
• DevOps: Solid experience as a DevOps Engineer in a 24x7 uptime Amazon AWS environment, including automation experience with configuration management tools.
• Infra automation: Experience in Terraform/Ansible
• Scripting Skills: Strong scripting (e.g. Python) and automation skills.
• Operating Systems: Linux system administration and strong shell scripting skills
• Monitoring Tools: Experience with web servers (e.g. Nginx).
• Problem Solving: Ability to analyze and resolve complex infrastructure resource and application deployment issues.

Desired Skills (Not essential but beneficial to have):

• DB Skills: Basic DB administration experience - Cassandra, RDS, MySQL
• Search engines: Experience with search engines such as Apache Solr/Elastic Search
• Version Control: Experience administrating version control systems such as Git

Example Responsibilities:

• Build and optimize model serving infrastructure with a focus on inference latency and cost optimization
• Architect efficient inference pipelines that balance latency, throughput, and cost across various acceleration options
• Develop monitoring and observability solutions for ML systems
• Collaborate with ML Engineers to establish best practices for optimized model deployment
• Implement cost-efficient, enterprise-scale solutions
• Collaborate in a cross-functional, distributed team for continuous system improvement
• Work with MLEs, QA Engineers, and DevOps Engineers
• Evaluate and implement new technologies and tools
• Contribute to architectural decisions for distributed ML systems

Experience and Qualifications:

• 5+ years of experience in software engineering with Python
• Experience with ML frameworks, particularly PyTorch
• Experience optimizing ML models with hardware acceleration (AWS Neuron , ONNX, TensorRT)
• Experience with AWS ML services and hardware-accelerated instances (Sagemaker, Inferentia,Trainium)
• Proven experience building and operating AWS serverless architectures
• Deep understanding of event-driven processing patterns, SQS/SNS and serverless caching solutions
• Experience with containerization using Docker and orchestration tools
• Strong knowledge of RESTful API design and implementation
• Proficiency in writing good quality & secure code and be familiar with static code analysis tools
• Excellent analytical, conceptual and communication skills in spoken and written English
• Experience applying Computer Science fundamentals in algorithm design, problem solving, and complexity analysis

Great to have Experience and Qualifications:

• Experience with any of the following: model compilation and quantization, performance profiling and benchmarking ML inference systems
• Experience working in regulated industries with strict compliance requirements for cloud-native solutions

• Bachelor’s degree in computer science, Data Science, Information Systems, or a related field  
• 8-10 years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering  
• Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure  
• Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn  

We are looking for a hands-on Senior AWS Cloud Engineer to lead the infrastructure build, optimization, automation, and production deployment of a Multi-Agent AI Chatbot Platform hosted on AWS. The development environment is already in place, and the successful candidate will drive the solution through testing, integrations, and production go-live.

Key Responsibilities

• Review, validate, and optimize existing Terraform code and AWS infrastructure.
• Establish and manage integrations with enterprise platforms such as ServiceNow, Workday, and other third-party systems.
• Design, build, and support secure, scalable, and highly available AWS environments.
• Implement and automate CI/CD pipelines and Infrastructure-as-Code practices.
• Lead infrastructure testing, performance tuning, and production readiness activities.
• Drive deployment and operationalization of the platform in the Production environment.
• Implement cloud governance, security, monitoring, and FinOps best practices.
• Troubleshoot and resolve complex cloud infrastructure issues.

Required Skills & Experience

• 10+ years of IT experience with strong expertise in AWS Cloud Engineering.
• Proven experience designing, deploying, and managing AWS production environments.
• Strong hands-on experience with Terraform and Infrastructure-as-Code.
• Experience with CI/CD pipeline automation and DevOps practices.
• Expertise in AWS services including VPC, IAM, EC2, S3, Lambda, CloudWatch, and networking.
• Experience in performance optimization, reliability, and cloud cost management (FinOps).
• Strong scripting and automation skills.
• Experience integrating enterprise applications through APIs and secure connectivity patterns.

Preferred Skills

• Experience supporting AI/GenAI, chatbot, or multi-agent platforms.
• AWS Certifications (Associate/Professional).
• Banking or Financial Services domain experience.

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day.

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI/ML Ops Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

• Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines
• Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
• CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools
• Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
• Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable
• Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.
• Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable
• Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
• Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.
• Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.
• Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
• Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
• Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
• Perform other duties as assigned

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Solution handling large scale structured and unstructured data from varied data sources
• Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
• Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
• In depth experience in System design, AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python and SQL
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Legally eligible to work in India on an ongoing basis

Get to Know Us:

At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.

Equal Opportunity Employer:

Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, India, and Singapore. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information. 

If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.

Job application link : https://grnh.se/z7qx2ehx1us

Cloud Infrastructure Engineer – BANG | 10+ Years

Location: Bangalore

Experience: 10+ Years

Job Description:

• Design, implement, and manage cloud infrastructure across AWS/Azure/GCP environments.
• Strong experience in cloud architecture, compute, storage, networking, and security.
• Manage VMs, VPC/VNet, load balancers, DNS, DHCP, firewalls, and IAM.
• Hands-on experience with Windows/Linux servers, VMware, virtualization, and infrastructure operations.
• Automate infrastructure provisioning and configuration using Terraform, Ansible, or similar tools.
• Monitor infrastructure performance, availability, and capacity using tools such as Grafana, Prometheus, or CloudWatch/Azure Monitor.
• Handle incident management, troubleshooting, disaster recovery, backup, and high-availability requirements.
• Work with cross-functional teams to support cloud migration, infrastructure upgrades, and production environments.
• Ensure infrastructure follows security, compliance, and operational best practices.

Must-Have Skills:

Cloud Infrastructure | AWS/Azure/GCP | Networking | Linux/Windows | VMware | Terraform | Ansible | DNS/DHCP | IAM | Monitoring | Backup & DR