Lead - Cloud Engineering (AWS / Azure) at Mango Sciences · Remote only · 10 - 15 years · ₹30L - ₹35L / yr · Raised funding · Remote only · Posted 9 Sep 2026

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).

About Mango Sciences
About
Mango Sciences is a leading emerging market data science company connecting millions of underrepresented patients to precision medicine. The company’s Querent™ platform utilizes industry-leading AI analytics to transform deep clinical data into key insights that drive global health improvements. Mango Sciences is currently partnering with hospitals to understand the health data of individuals in India and other emerging markets to drive advancement in patient care and drug discovery for all populations.
Website- https://mangosciences.com/
Industry- Health Technology
Headquarters - Boston, Massachusetts
Tech stack
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Required Skills & Qualifications
- Experience: 10+ years in Cloud Engineering, Infrastructure, or DevOps, with strong hands-on GCP experience.
- GCP Expertise: GKE, Compute Engine, IAM, VPC, Cloud Storage, Cloud SQL, Cloud Run, Cloud Functions, and Load Balancing.
- Kubernetes & Containers: GKE, Docker, Kubernetes networking, Helm, and troubleshooting.
- DevOps & IaC: Azure DevOps, Terraform, CI/CD pipelines, and infrastructure automation.
- Scripting: Python, Bash, or PowerShell.
- Security & Operations: Cloud security, IAM, monitoring, incident management, and cost optimization.
- Leadership & Ownership: Proven experience in team leadership, cross-functional collaboration, stakeholder management, managing multiple product-line deliverables, and handling competing priorities and ad hoc requests.
- Additional Advantage: Experience with Microsoft Azure.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
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
Role Overview: Take full ownership of infrastructure architecture, scaling, and uptime. Establish the technical roadmap, shape and formalize the SRE function, and coach engineers. Design, deploy, and run AI-scale infrastructure that enables real-time healthcare workflows.
Serve as a Founding Member, owning end-to-end infrastructure capabilities and introducing AI-first DevOps, SRE, and MLOps best practices, with direct collaboration alongside the Founder, Co-Founder, and Head of Engineering.
Key Responsibilities:
Architecture & Platform
- Design scalable, secure, cost-efficient AWS/GCP architectures for AI and healthcare workloads
- Lead IaC standards and reusable modules org-wide; own GitOps practices
- Architect optimized Kubernetes (EKS/GKE) for HA, scale, and GPU workload orchestration
Reliability Engineering
- Define and drive reliability targets (SLOs/SLIs); establish SRE practice
- Lead incident management, RCA, and blameless post-mortems for critical systems
- Partner on infrastructure hardening and compliance (SOC 2, HIPAA)
AI-First Engineering
- Lead AI/ML inference and GPU infrastructure scaling in production
- Evaluate and introduce AI tooling, platforms, and automation best practices
- Contribute to LLM deployment pipelines and AI systems reliability
Leadership & SDLC
- Mentor L1/L2 engineers; influence cross-team infrastructure decisions
- Drive DevSecOps maturity across the SDLC (policy-as-code, SBOM, supply-chain security)
- Evaluate and introduce new tooling and platforms
Key Requirements:
- 4–8 years infrastructure/platform/DevOps/SRE
- Deep expertise in AWS & GCP large-scale production systems
- Advanced Kubernetes (cluster design, multi-tenant ops, resource quotas)
- AI/ML inference or GPU infrastructure scaling (production track record)
- Strong Terraform / equiv. and GitOps practices
- Python, Go, or Bash scripting and automation
- Track record in scale, reliability, and cost efficiency
- Lead incident response and on-call practices
Nice-to-Have
- LLM Gateway architecture and optimization
- Zero-trust networking and advanced security/compliance (SOC 2, HIPAA)
- DevSecOps maturity: SBOM, supply-chain security, policy-as-code
- Open-source contributions or platform-team leadership
Why This Role?
- Build infrastructure and products powering real-world healthcare AI
- Work with AI-native engineering teams using cutting-edge tools (Claude Code, Cursor, Copilot)
- Mission-driven impact — improve patient outcomes and save thousands of staff hours
- High ownership, rapid learning, and significant career upside
- Global collaboration across India and the US
- Seed-stage growth — scale from Seed to Series A alongside the team
- Founding Member role and own the entire infrastructure capabilities, including bringing best AI-first practices in DevOps, SRE and MLOps; direct access to work with the Founder, Co-Founder and Head of Engineering
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.
Job Title : Senior AWS DevSecOps & AI Platform Engineer
Experience Required : 5+ Years in AWS / Cloud Engineering
Terraform Experience : 4+ Years
Location : Gurugram
Work Mode : Onsite
Employment Type : Full-time
About the Role :
We are looking for an experienced Senior AWS DevSecOps & AI Platform Engineer with strong expertise in AWS cloud infrastructure, Kubernetes, Infrastructure as Code (IaC), CI/CD automation, cloud security, and database administration.
The ideal candidate will be responsible for designing and maintaining secure, scalable, reliable, and cost-efficient cloud environments while supporting microservices-based applications and implementing DevSecOps best practices. The role also involves building and deploying AI agents using Amazon Bedrock and Bedrock AgentCore, along with managing enterprise development and collaboration tools.
Mandatory Skills :
AWS (EC2, EKS, ECS, Lambda, S3, CloudWatch), Kubernetes, Terraform, Jenkins, Bitbucket Pipelines, CI/CD, DevSecOps, AWS Security Services (IAM, WAF, GuardDuty, Security Hub, KMS, Secrets Manager), Microservices, Helm, PostgreSQL, Oracle SQL, RDS, Jira, Confluence, Amazon Bedrock, Bedrock AgentCore, AWS Networking, and Cloud Cost Optimization.
Key Responsibilities :
- AWS Cloud Infrastructure : Design, implement, and maintain AWS infrastructure with a focus on scalability, availability, security, reliability, and cost optimization.
- Microservices & Containerization : Manage and support distributed microservices architectures, including deployment, monitoring, troubleshooting, performance optimization, service meshes, and API gateways.
- Kubernetes Administration : Administer and optimize Kubernetes clusters, including Amazon EKS and self-managed environments, covering upgrades, networking, workload management, scaling, and resource optimization.
- Cloud Security & Compliance : Implement and manage AWS security services, including IAM, GuardDuty, Security Hub, WAF, KMS, Secrets Manager, AWS Config, and CloudTrail.
- DevSecOps Implementation : Integrate security testing, vulnerability scanning, container security, and compliance-as-code tools into CI/CD pipelines.
- CI/CD & Source Control : Manage Bitbucket repositories, branching strategies, permissions, and Bitbucket Pipelines. Build and optimize Jenkins pipelines using declarative and scripted approaches.
- Infrastructure as Code : Develop and maintain Terraform modules, manage remote state and workspaces, detect infrastructure drift, and implement reusable infrastructure provisioning practices.
- Database Administration : Provision, manage, secure, and optimize AWS RDS databases, particularly PostgreSQL and Oracle, including backups, replication, patching, performance tuning, and migrations.
- Jira & Confluence Administration : Manage projects, workflows, automation rules, permissions, user access, spaces, schemes, and plugins.
- Monitoring & Reliability : Define and monitor SLIs, SLOs, and SLAs; implement observability best practices; and participate in incident management, root cause analysis, and post-incident reviews.
- AI Agent Development : Design, build, and deploy AI agents using Amazon Bedrock and Bedrock AgentCore, including agent runtime, memory, tools, gateway integration, identity and access management, guardrails, and lifecycle management across environments.
- Cloud Connectivity : Support hybrid cloud connectivity using AWS Direct Connect, VPN, and Transit Gateway.
- Cost Optimization : Apply FinOps practices to monitor cloud expenditure, optimize resource utilization, and improve infrastructure efficiency.
- API Integrations : Integrate third-party APIs while implementing authentication, rate limiting, error handling, and webhook management.
Required Skills & Qualifications :
- 5+ years of hands-on experience with AWS cloud services, including EC2, ECS, EKS, Lambda, ALB, CDN, S3, CloudWatch, Amazon Bedrock, and Bedrock AgentCore.
- Strong understanding of AWS networking, multi-account strategies, landing zone architecture, and hybrid connectivity.
- 4+ years of practical experience with Terraform, including module development, remote state management, workspaces, drift detection, and state operations.
- Extensive experience administering Kubernetes, preferably Amazon EKS, including Helm, Kustomize, operators, RBAC, network policies, autoscaling, and multi-tenancy.
- Proven experience managing distributed microservices, service meshes, API gateways, and inter-service communication.
- Strong knowledge of AWS security services, including IAM, Service Control Policies (SCPs), WAF, KMS, Secrets Manager, AWS Config, and CloudTrail.
- Experience implementing least-privilege access, zero-trust principles, and cloud security compliance controls.
- Hands-on experience integrating DevSecOps tools such as Snyk, Trivy, Checkov, and SonarQube into CI/CD pipelines.
- Understanding of OWASP security principles, CIS benchmarks, vulnerability management, and container security.
- Proficiency in Bitbucket repository administration, branch permissions, and YAML-based Bitbucket Pipelines.
- Strong experience developing and maintaining Jenkins CI/CD pipelines, shared libraries, plugins, and build agents.
- Experience administering AWS RDS databases, particularly PostgreSQL and Oracle SQL, including backup, replication, performance tuning, and migration activities.
- Experience administering Jira and Confluence, including workflows, permissions, automation, and plugin management.
- Working knowledge of Azure services, particularly Web Apps and Logic Apps/Workflows.
- Practical experience with Amazon Bedrock, including model invocation, guardrails, and AI agent development and deployment using Bedrock AgentCore.
- Understanding of third-party API integration, authentication mechanisms, rate limiting, error handling, and webhook management.
- Familiarity with FinOps practices and cloud cost optimization.
Good-to-Have Skills :
- Additional Azure experience, including networking, Azure SQL Managed Instance, and Azure Kubernetes Service (AKS).
- Hands-on experience with AI-driven Development Lifecycle (AI-DLC) methodologies and tools such as Kiro.
Relevant certifications, such as :
- AWS Certified Solutions Architect
- AWS Certified DevOps Engineer – Professional
- AWS Machine Learning or Generative AI certifications
- Certified Kubernetes Administrator (CKA)
- HashiCorp Terraform certifications
Ideal Candidate Profile :
The ideal candidate is a hands-on cloud and DevSecOps professional who can manage enterprise-scale AWS infrastructure, automate deployments, strengthen security controls, troubleshoot complex distributed systems, and support AI agent development. Strong problem-solving skills, an automation-first mindset, and the ability to collaborate across development, security, and infrastructure teams are essential.
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.
Role Overview:
Virtana is seeking a Senior Manager, Global DevOps Engineering to lead the global team, platforms, and infrastructure that enable rapid, reliable product delivery. This leader will own DevOps strategy and execution across SaaS (GCP heavy, with presence in AWS and Azure) & on-premises Infrastructure, CI/CD, automation, reliability, security, and developer productivity, while aligning distributed teams and cross-functional stakeholders around measurable business outcomes.
Key Accountabilities:
- Strategy and Execution: Set the global DevOps roadmap and operating model, aligned with product, engineering, and business priorities.
- Global Leadership: Build, lead, and develop a high-performing team across geographies, with clear accountability and consistent engineering practices.
- Cloud and Platform Ownership: Own the architecture, reliability, security, scalability, and cost efficiency of global GCP and hybrid infrastructure.
- Software Delivery: Advance secure, standardized CI/CD, Infrastructure as Code, automation, and self-service capabilities to accelerate delivery and improve quality.
- Operational Excellence: Establish SLOs, observability, incident response, disaster recovery, governance and metrics for critical platforms. Own the global on-call program and serve as the escalation point for major incidents from SaaS Infra/DevOps side.
- Executive Partnership: Align stakeholders on priorities, investments, dependencies, and risk; communicate outcomes and tradeoffs to senior leadership.
Required Qualifications:
- 15+ years in software engineering, infrastructure, cloud operations, or DevOps, including 5+ years leading senior or management-level teams.
- Proven success in leading global teams across geographies, cultures, and time zones.
- Deep expertise in GCP architecture, security, networking, reliability, and cost governance.
- Demonstrated ownership of enterprise CI/CD, build and release automation, and modern software delivery practices.
- Strong experience with Terraform or equivalent Infrastructure as Code, Kubernetes, containers, observability, SRE, and disaster recovery.
- Track record operating secure, resilient global infrastructure for fast-paced development and release environments.
- Daily hands-on use of AI tools (e.g., Claude) for IaC, CI/CD pipelines and incident response, with a record of driving AI adoption that improves delivery speed and quality.
- Executive-level communication and stakeholder leadership, with the ability to align priorities, resolve tradeoffs, and develop strong leaders.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
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










