Lead - Cloud Security and Reliability Engineer

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

• 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

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).

Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent experience).

3+ years of hands-on experience with Microsoft Azure, including IaaS, PaaS, networking, identity (Entra ID), and governance services.

2+ years of experience with DevOps tooling and practices, including CI/CD pipelines (Azure DevOps or GitHub Actions), Infrastructure as Code (Terraform, Bicep, or ARM), and version control (Git).

2+ years' experience in infrastructure design, platform engineering, or architecture.

Strong proficiency with automation and scripting — PowerShell, Azure CLI, Python, or Bash.

Solid understanding of containerisation (Docker) and familiarity with orchestration platforms (Azure Kubernetes Service).

Deep understanding of cloud architecture, deployment patterns, and management best practices, including the Azure Well-Architected Framework.

Experience defining standards, governance frameworks, and reference architectures for cloud platform consumption.

Strong knowledge of networking concepts, storage configurations, virtualisation technologies, and disaster recovery/backup design for hybrid environments.

Experience with Azure DevOps (Repos, Pipelines, Boards, Artifacts) or equivalent platforms.

Familiarity with identity and access management (IAM), including Entra ID, RBAC, PIM.

Strong understanding of security, compliance requirements, and IT governance frameworks (ITIL, COBIT, or similar).

Preferred

🚀 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

As a DevOps Engineer at YOYO, 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.

If you are Interested DM me on LinkedIn - Saquib Mundagnur

 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

 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

Tasks & Responsibilities: (Major task and role person will have to perform – list all the relevant points)    

Together with the Business Cloud Services team, you will design, deploy, and operate a cloud‑native Kubernetes PaaS platform on Azure, ensuring high availability, security, and operational excellence.

Your main duties include:

·      Drive cloud‑native automation and self‑service capabilities, ensuring platform security, availability, and disaster recovery readiness

·      Design, operate, and continuously improve Kubernetes clusters and PaaS environments on Azure / AKS

·      Collaborate closely with development teams on deployment strategies, operational requirements, and platform integration

·      Review and maintain infrastructure‑as‑code configurations, CI/CD pipelines, and cloud‑native deployments

·      Build and maintain CI/CD pipelines using Azure DevOps

·      Implement and operate infrastructure‑as‑code solutions using Terraform, Helm, and Ansible

·      Manage containerized workloads and orchestration across cloud‑native environments

·      Set up, operate, and enhance monitoring, logging, and alerting stacks using tools such as Prometheus and Grafana

·      Coordinate with support teams on platform incidents, escalations, and post‑incident analysis

·      Contribute to incident response, continuous improvement, and operational stability

·      Support the development and refinement of DevOps practices, runbooks, and operational standards

·      Actively contributes to improving developer experience and platform reliability

Education & Trainings + Certifications: (Basic & Professional)

·      Bachelor’s degree (Preferably engineering graduate)

·      Azure Solutions Architect Expert Certification is a plus.

·      (optional) ITIL Foundation 

Technical know-how: (Mention the technology on which person must be experienced)

Mandatory

o  Bachelor’s degree in computer science, Information Systems, or a related field

o  5+ years of relevant professional experience in DevOps, Cloud Engineering, or Platform Engineering roles

o  Strong Linux system administration skills for operating production‑grade cloud‑native platforms

o  Proven experience with Microsoft Azure, including AKS and Azure DevOps tooling

o  Strong expertise in Kubernetes, including cluster operations, RBAC, networking, and storage

o  Hands‑on experience with container technologies such as Docker and container registries

o  Proficiency with Terraform, Helm, Ansible, and PowerShell

o  Experience building and operating CI/CD pipelines using Azure DevOps or equivalent tools

o  Cloud‑native monitoring and observability experience using Prometheus, Grafana, and alerting pipelines

o  Solid understanding of security and compliance requirements such as PCI DSS and SOC2

o  Scripting skills for automation and tooling (Bash, Python, PowerShell)

o  Practical experience using Git for version control

o  Excellent communication skills in English (Spanish is a plus)

o  Automation‑first mindset and strong collaboration skills within Agile teams

Good to know

Principles of Agile Software Development.

·      GitHub Actions, GitLab CI, Jenkins, Azure DevOps

·      Containers: Docker, Kubernetes (EKS / AKS / GKE)

·      Configuration Management: Ansible

Job Description

We are looking for an Azure Cloud & Observability Engineer with strong experience in Azure infrastructure and enterprise monitoring tools such as Splunk, Grafana, and AppDynamics.

Responsibilities

• Design, deploy, and manage Azure cloud infrastructure and services.
• Monitor application and infrastructure performance using Splunk, Grafana, and AppDynamics.
• Configure dashboards, alerts, health rules, and monitoring metrics.
• Perform log analysis, troubleshooting, and root-cause analysis for production issues.
• Implement observability solutions for applications, cloud infrastructure, and services.
• Automate monitoring and operational activities using scripting.
• Support incident, problem, and change management processes.
• Collaborate with development, DevOps, and SRE teams to improve system reliability.
• Maintain monitoring standards, documentation, and operational procedures.

Primary Skills

• Microsoft Azure
• Splunk
• Grafana
• AppDynamics
• Cloud Monitoring & Observability
• Application Performance Monitoring (APM)
• Log Analysis & Troubleshooting

Secondary Skills

• Azure Monitor / Log Analytics
• Azure VMs, Storage, Networking
• Linux
• Python / PowerShell / Shell Scripting
• CI/CD
• Git
• ITIL / ServiceNow

Job Description

We are looking for an Azure Cloud & Observability Engineer with strong experience in Azure infrastructure and enterprise monitoring tools such as Splunk, Grafana, and AppDynamics.

Responsibilities

• Design, deploy, and manage Azure cloud infrastructure and services.
• Monitor application and infrastructure performance using Splunk, Grafana, and AppDynamics.
• Configure dashboards, alerts, health rules, and monitoring metrics.
• Perform log analysis, troubleshooting, and root-cause analysis for production issues.
• Implement observability solutions for applications, cloud infrastructure, and services.
• Automate monitoring and operational activities using scripting.
• Support incident, problem, and change management processes.
• Collaborate with development, DevOps, and SRE teams to improve system reliability.
• Maintain monitoring standards, documentation, and operational procedures.

Primary Skills

• Microsoft Azure
• Splunk
• Grafana
• AppDynamics
• Cloud Monitoring & Observability
• Application Performance Monitoring (APM)
• Log Analysis & Troubleshooting

Secondary Skills

• Azure Monitor / Log Analytics
• Azure VMs, Storage, Networking
• Linux
• Python / PowerShell / Shell Scripting
• CI/CD
• Git
• ITIL / ServiceNow