Lead - Cloud Engineering (AWS / Azure)

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

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

• 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

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.

We are looking for a Lead DevOps Engineer with strong hands-on experience in AWS, GCP, CI/CD, Kubernetes, Docker, Terraform, Pulumi and DevSecOps. The candidate will lead DevOps teams, drive technical delivery with client stakeholders, design scalable and secure cloud infrastructure, and establish best practices for automation, deployment, reliability, and cost optimization across cloud environments.

### Key Responsibilities

* Lead and mentor DevOps engineers, drive technical execution, and ensure timely delivery of client requirements.

* Engage with client teams and architects to understand requirements, provide technical guidance, and drive solution design and implementation.

* Design, implement, and optimize CI/CD pipelines, GitOps workflows, and automated release processes.

* Architect and manage cloud infrastructure across AWS and GCP (Azure optional) using Infrastructure as Code.

* Lead containerization and orchestration initiatives using Docker, Kubernetes, and Helm.

* Drive DevSecOps, observability, SRE practices, disaster recovery, and cloud cost optimization.

* Troubleshoot complex production issues, drive root cause analysis, and ensure system reliability, security, and performance.

* Collaborate with Development, QA, Security, Architecture, and client teams to drive engineering standards and continuous improvement.

### Mandatory Skills

* 7-9 years of experience in DevOps, Cloud Engineering, or Platform Engineering, including team leadership and client-facing responsibilities.

* Strong hands-on experience with AWS and GCP, including cloud infrastructure, networking, security, and managed services.

* Expertise in CI/CD tools such as Jenkins, Azure DevOps, GitLab CI/CD, GitHub Actions, or equivalent platforms.

* Strong experience with Docker, Kubernetes, Helm, and managed Kubernetes services such as AKS, EKS, or GKE.

* Hands-on expertise in Terraform and Ansible, with experience in Infrastructure as Code and configuration management.

* Experience with GitOps practices and tools such as Argo CD or Flux.

* Strong understanding of Git, branching strategies, release management, and deployment automation.

* Experience implementing DevSecOps practices, including security scanning, secrets management, and vulnerability management.

* Experience with monitoring, logging, alerting, production troubleshooting, and root cause analysis.

* Proficiency in Linux administration, networking fundamentals, and Bash/Python/PowerShell scripting.

* Proven ability to lead teams, manage priorities, communicate with clients, and drive technical decisions independently.

independently.

### Preferred Skills

* Knowledge of SAST/DAST, SBOM, software supply chain security, and security policy enforcement.

* Experience with observability tools such as Prometheus, Grafana, ELK Stack, Datadog, or Splunk.

* Experience with cloud migrations, hybrid environments, disaster recovery, high availability, and cost optimisation.

* Knowledge of service mesh technologies such as Istio or Consul, and API gateways or application gateways.

* Experience with enterprise cloud security, IAM, network security, and infrastructure

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.

🚀 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

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.