Lead - Cloud Engineering (AWS / Azure)

Cloud Expertise(Azure):

• Strong understanding of cloud services and resources like AI services, webapp, database, including monitoring tools like Azure Monitor and Log Analytics.

• Experience with Infrastructure as Code (IaC) tools such as Arm template / Bicep/Terraform.

• Deep understanding of Networking concepts(DNS, DHCP , Hub and Spoke).

• Understanding on policies and security aspects of cloud.

Kubernetes & Helm:

• In-depth knowledge of Kubernetes concepts such as pods, services, ingress, config maps, and secrets.

• Understand of Kubernetes templates and its deployment.

• Proficiency with Helm/ Kustomize or equivalent for Kubernetes package management and deployment automation.

• Implement Kubernetes best practices, including security, networking, and scaling.

• Concepts of Docker and Containers

CI/CD & Programming:

• Hands-on experience with YAML-based CI/CD pipelines (e.g., Azure DevOps, GitHub Actions).

• Familiarity with scripting and automation tools such as PowerShell, Azure CLI, or Bash.

• Proven skill in python programming and concepts.

Monitoring and Observability:

Expertise in creating and managing Grafana dashboards for visualizing metrics and logs.

• Knowledge of Log Analytics & Azure Application Insights for performance monitoring and tracing.

Senior Cloud Site Reliability Engineer (CSRE) – Azure

About Searce:

Searce is an AI-native, engineering-led modern technology consultancy that empowers

clients to futurify their businesses by delivering real, intelligent business outcomes. As a

trusted partner for over 3,000 clients globally, Searce specializes in cloud modernization,

data engineering, applied AI, and robust cloud platform security. Driven by a "HAPPIER"

cultural mindset and our proprietary evlos problem-solving framework, we eliminate

bureaucratic fluff to build working prototypes fast and scale enterprise production

environments intelligently. We don't just fix systems; we leverage multi-cloud technologies

to transform client operations into distinct competitive advantages.

Position Overview:

We are looking for a high-caliber Senior or Lead Cloud Site Reliability Engineer (CSRE) to

architect, secure, and stabilize next-generation hybrid and multi-cloud environments.

Operating at the intersection of infrastructure design, security compliance, and production

operations, you will serve as the technical Subject Matter Expert (SME) across GCP, Azure,

and AWS.

Whether optimizing a microservice mesh on GKE, tuning autoscaling on AKS, or driving a

massive disaster recovery drill across AWS regions, your focus will be absolute reliability. For

the Lead path, you will couple this deep engineering toolkit with stakeholder management

and mentorship to drive an elite operational culture.

Experience & Level Expectation:

Years of Experience: 3 to 10 years of intensive, hands-on production operations

experience in a dedicated DevOps, Cloud Platform Engineering, or SRE role.

Associate level (3-5 Years): Expected to show flawless execution of IaC, advanced

triaging of infrastructure failures, and ownership of the CI/CD and deployment

lifecycles.

Intermediate level (5-10 Years): Expected to take architectural ownership, serve as

primary Incident Commander for complex outages, design cross-cloud governance

frameworks, and act as a reliable bridge between technical teams and client

leadership.

Key Responsibilities & Role Expectations:

Multi-Cloud Platforms & Orchestration: Design, configure, and maintain

production-grade Kubernetes clusters across major platforms (AKS).

Manage advanced network routing, service meshes (e.g., Istio), and multi-tenant

isolation.

Infrastructure as Code (IaC) & GitOps: Build declarative, enterprise-grade, reusable

infrastructure components using Terraform or Crossplane. Standardize automated

environment provisioning to eliminate configuration drift across multi-branch

environments.

Incident Management & Reliability (SRE): Own and optimize the production on-call

rotation. Lead rapid mitigation strategies for Sev-1/Sev-2 system outages, reducing

Mean Time to Recovery (MTTR) through centralized log and metric correlation.

Root Cause Analysis (RCA): Facilitate rigorous, blameless post-incident reviews to

identify core architectural vulnerabilities and establish long-term fixes preventing

recurrence.

Lifecycle, Patching & Upgrades: Plan and execute zero-downtime cluster upgrades,

operating system patching strategies (Linux/Windows), database lifecycle updates,

and multi-region Disaster Recovery (DR) failover drills.

Core Core Operations & Legacy Integration: Manage enterprise-level hybrid

networking architecture (VPCs, Firewalls, Load Balancers, DNS routing, and DHCP

configurations) while effectively connecting cloud native services to legacy

infrastructures like Active Directory.

Security & Governance: Embed Zero Trust policies, secure secrets management

(Secrets Manager/Key Vault), and continuous vulnerability patching into the

automated SDLC pipeline.

Required Technical Skills:

- Microsoft Azure: Azure Virtual Machines, Virtual Networks, Azure Active Directory, Azure Update Management.

- Containers & Orchestration

• Production-level management of GKE, AKS, and EKS.
• Advanced mastery of Docker, Helm, Kubernetes StatefulSets, Pod Disruption

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)

• Strong hands-on experience in Microsoft Azure Cloud.
• Good understanding of Azure services such as Compute, Storage, Event Hub, Event Subscription, Storage Queue, and PaaS services.
• Basic understanding of Azure AI Foundry and AI-related Azure service setup.
• Good Azure networking basics: VNet, subnet, routing, and basic troubleshooting.
• Strong knowledge of Terraform, especially:
• Terraform state
• plan / apply
• troubleshooting failures
• migration risks
• Terraform Enterprise concepts
• Strong Python coding capability, not just basic scripting.
• Experience using Python for API integration, automation, JSON/YAML handling, and internal tooling.
• Good understanding of CI/CD pipelines.
• Ability to troubleshoot pipeline failures.
• Comfortable with YAML and JSON.
• Ability to troubleshoot Azure infrastructure/platform issues.
• Ability to collect logs/evidence and coordinate with network/app/Microsoft support teams.
• Basic awareness of agentic AI / LLM concepts.
• Awareness of security and cost best practices.

Good to Have Skills

• Hands-on experience with Harness.
• Hands-on experience with Terraform Enterprise.
• Exposure to LangGraph / LangChain.
• Exposure to agentic AI workflows or skill creation.
• Exposure to Claude or enterprise LLM integrations.
• Knowledge of Azure ML Workspace, model registry, and managed endpoints.
• MLOps / LLMOps knowledge.
• FinOps / Azure cost optimization experience.
• Azure certifications: AZ-104, AZ-305, AZ-400, AZ-500.

Screening Priority:

Azure Cloud + Terraform + Python Coding + CI/CD Troubleshooting + YAML/JSON + Basic Agentic AI Awareness

🚀 Hiring: Senior Azure Platform Engineer | Azure | Terraform | Kubernetes

📍 Location: India

💼 Employment: Full-Time | Long-Term

🎯 Experience: 10+ Years | 8+ Years Hands-on Azure

🔑 What We’re Looking For

▪️ Strong expertise in Azure Cloud Platform & Landing Zone Architecture

▪️ Advanced hands-on experience with Terraform & reusable IaC modules

▪️ Expertise in Kubernetes, Helm & container platforms

▪️ Strong understanding of Azure Networking, Entra ID, RBAC & Azure Policy

▪️ Experience with GitHub, GitHub Actions / Azure Pipelines & CI/CD

▪️ Hands-on GitOps & ArgoCD experience

▪️ Strong observability skills with Prometheus, Grafana & Azure Monitor

▪️ Experience designing and supporting microservices architectures

▪️ Knowledge of security, policy-as-code and IaC security scanning

▪️ Exposure to Azure Arc / Azure Local / Azure Stack HCI is a plus

AWS / Kubernetes / OpenShift / Linux –

Location: Bangalore

Experience: 7–10 Years

Mandatory Skills:

• Strong hands-on experience with AWS
• Experience in Kubernetes & OpenShift
• Strong knowledge of Linux administration
• Experience with Docker & containerization
• Knowledge of CI/CD pipelines and DevOps practices
• Troubleshooting, monitoring, and deployment experience

Role: Cloud/DevOps Engineer – AWS, Kubernetes & OpenShift

WowPe is a leading fintech company revolutionizing the way businesses handle financial transactions. Our suite of innovative products includes a secure Payment Gateway for seamless online transactions, robust Payouts solutions to streamline bulk payments, and a versatile Point of Sale (POS) system for efficient in-store transactions. At WowPe, we’re dedicated to providing user-friendly, scalable, and reliable solutions that empower businesses to grow and succeed in today’s fast-paced digital economy.

We are looking for a highly skilled Cloud Infrastructure & Cloud Network Engineer to design, build, and manage secure, scalable hybrid cloud environments at WowPe. This role will focus on cloud networking, hybrid connectivity, infrastructure automation, security, reliability, and performance across on-prem and cloud platforms (AWS/Azure). You will play a critical role in ensuring high availability, security, and performance of our fintech platforms.

A Day in the Life

• Design and review cloud network architectures (VPC/VNet, routing, segmentation)
• Troubleshoot latency, connectivity, VPN, and performance issues
• Work with DevOps and application teams to support deployments and scalability
• Automate infrastructure provisioning and security guardrails
• Monitor network health, traffic flow, and system performance
• Ensure security, compliance, and disaster recovery readiness
• Support hybrid connectivity between on-prem data centers and cloud environments.

Key Responsibilities

Cloud Networking & Hybrid Architecture

• Design and implement VPC/VNet architectures, subnetting, routing tables, NAT, gateways, and secure segmentation
• Build and manage hybrid connectivity between on-prem data centers and cloud using Site-to-Site VPN, ExpressRoute, Direct Connect
• Configure and manage Layer 4 & Layer 7 load balancers for high availability and traffic distribution
• Architect DNS, CDN, and edge networking strategies for low-latency global access

Security & Zero-Trust

• Implement Zero-Trust networking using security groups, NACLs, identity-aware proxies, mTLS
• Design secure access controls and network isolation
• Work closely with security teams to ensure PCI, ISO, SOC compliance readiness

Automation, Platform & Reliability

• Automate infrastructure provisioning using Infrastructure as Code (Terraform/ARM/CloudFormation)
• Build self-healing, auto-scaling architectures with health checks and fault tolerance
• Support and manage Kubernetes clusters (EKS/AKS) including networking and service communication
• Integrate infra with CI/CD pipelines for safe and frequent deployments

Operations & Observability

• Perform advanced troubleshooting for latency, packet loss, MTU, routing loops
• Implement and manage monitoring, logging, and observability (Prometheus, Grafana, ELK, Azure Monitor, CloudWatch)
• Design and maintain disaster recovery architectures, multi-region networking, and replication strategies
• Ensure high availability, performance optimization, and cost efficiency

Basic Qualifications & Skills

• 4+ years of experience in Cloud Infrastructure & Cloud Networking
• Strong hands-on experience with AWS and/or Azure
• Deep understanding of VPC/VNet, routing, NAT, gateways, load balancers, DNS
• Experience with Hybrid connectivity (VPN, ExpressRoute, Direct Connect)
• Solid knowledge of network security, firewalls, access control, segmentation
• Hands-on experience with Infrastructure as Code (Terraform preferred)
• Experience in monitoring, troubleshooting, and incident handling
• Strong understanding of high availability, DR, and performance optimization

Preferred Qualifications

• Experience in fintech, BFSI, or high-compliance environments
• Exposure to Zero-Trust architecture and security best practices
• Experience with Kubernetes (EKS/AKS), service mesh, microservices networking
• Familiarity with CI/CD pipelines and DevOps practices
• Knowledge of CDN, edge networking, and global traffic management
• Experience with compliance frameworks (PCI-DSS, ISO 27001, SOC2)
• Ability to design large-scale, resilient, production-grade architectures

We're hiring a Cloud Architect (Contract) to work with our Equity Partners who builds profitable growth by acquiring and operating enterprise software companies. Refining a proprietary operating model across 40+ acquisitions and two decades of hands-on experience, now supercharged by our patented agentic AI platform . In this role, you'll take full architectural control of our CI/CD, observability, and event streaming infrastructure, build the standards every new acquisition plugs into, and use AI-assisted automation to keep 20+ products reliable without proportionally scaling headcount.

Job title: Cloud/Platform Architect (SRE)

Type: Global Remote | Contract

What You Bring

• 8–12 years in platform engineering, DevOps, or SRE, with growing ownership over time
• Deep Terraform experience across multi-account, multi-env setups
• Real production experience with event streaming at scale
• Hands-on Grafana, Prometheus, Loki, and strong AWS depth (ECS, EKS, IAM, VPC, RDS)
• SRE fundamentals: SLOs, error budgets, on-call design, post-mortems
• Bonus: acquisition or greenfield platform-building experience

Roles and Responsibilities

• Own everything outside core AWS infra: CI/CD, observability, event streaming, deployment, incidents
• Define the standards every future acquisition will plug into
• Keep 20+ enterprise products running at serious scale (millions–billions of requests)
• Build self-service tooling so product teams never wait on you
• Use AI/automation to kill toil — not to replace engineering judgement

Ready to build the platform that scales an entire portfolio? — let's connect.

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

About the role

You will be a pivotal member of the leadership team, responsible for driving the company's product and platform strategy while overseeing engineering excellence across AI, data, platform, DevOps and infrastructure. This is a mission-critical role for an engineering leader who is both strategic and hands-on, and who can build scalable technologies for global enterprise clients in a fast-paced innovation ecosystem.

Reports to: CEO · Location: Bengaluru, India — hybrid, 3 days a week in office

What you will do

Technology & product leadership

• Define and drive the technology vision, architecture and long-term platform roadmap.
• Oversee the architecture, design and delivery of highly scalable enterprise systems.
• Ensure engineering excellence, velocity and reliability across the product lifecycle.

Engineering & platform management

• Lead platform engineering, product technology, DevOps, infrastructure and Quality Engineering.
• Build robust cloud-native systems using the Azure, AWS and GCP ecosystems.
• Oversee operational effectiveness, including uptime, production reliability and cost optimisation.

Innovation & AI strategy

• Spearhead Mission AI by developing scalable, production-grade AI/ML and GenAI capabilities.
• Own the GenAI/LLM solutions architecture.
• Core specialisation in AI agents and autonomous workflows, data extraction and intelligent automation.
• Direct hands-on architectural oversight of large language models, applied AI and multi-layered deep learning products.
• Extensive expertise in building intelligent document automation systems — similar in complexity to patent parsing, legal workflow automation and structured decision intelligence tools.

Technical leadership

• A proven track record overseeing product architecture, tech strategy and cross-functional engineering execution across core full-stack and AI platforms.
• Collaborate with executive leadership on business strategy, client requirements and product delivery.
• Build, mentor and scale high-performing engineering teams with a growth mindset.
• Establish a strong technology culture grounded in ownership, innovation and continuous learning.

What success looks like

• Mission AI: build a world-class AI system leveraging GenAI, ML and enterprise-grade data engineering.
• Hyper-scaling: architect and scale the platform to match global industry leaders in the IP space.
• Culture building: develop a strong engineering organisation with high ownership, performance and innovation DNA.

Qualifications & experience

• Preferably under 15 years of enterprise software engineering experience across B2B SaaS or technology-first companies; fewer is fine for an exceptional engineer.
• A proven track record of taking early-stage AI/ML prototypes and scaling them into robust enterprise SaaS platforms featuring multi-agent orchestration, complex workflows and decision intelligence.
• Experienced in building and mentoring agile, lean startup teams of full-stack and machine learning engineers from the ground up.
• Proven leadership in defining and executing technology strategy and platform roadmaps.
• Extensive cloud-native engineering experience with Azure, AWS and GCP.

Technical expertise

• Strong full-stack engineering background (Java, Python, JavaScript frameworks).
• Expertise with JS frameworks such as React, Angular and Node.js.
• Experience building and scaling distributed systems and microservices.
• Strong knowledge of databases (SQL, NoSQL), data modelling and unstructured data management.
• Strong understanding of Agile methodologies and tools (Atlassian, Git, CI/CD pipelines).

Behavioural & leadership competencies

• Product and delivery management expertise, end to end, including delivery and customer support.
• Excellent communication, with the ability to influence executive stakeholders.
• High technical proficiency combined with strong business acumen.
• Strong analytical and decision-making skills.