HYDERABAD · FULLTIME
Sr. DevOps Engineer

Cloudfulcrum
Hyderabad · onsite · Posted 2d ago
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Section · 01
About this role
> Sr. DevOps Engineer
Location: Hyderabad, INDIA
Work Mode: Hybrid
Skills: DevOps;Python;CI/CD;Azure
Experience in Years: 6
Type: Full Time
Life Sciences Cloud, Revenue Lifecycle Management and nCino each carry configuration, data dependencies and business journeys that must move-and be verified-with every release.
A Salesforce release is rarely just a collection of metadata. In an industry cloud, the change also carries business configuration, connected data, sequencing rules and critical journeys that have to remain intact from one environment to the next.
That distinction matters. A deployment can complete exactly as planned while the wider business release still contains unresolved risk: a configuration dependency moved out of sequence, target data is not ready, or a process that spans several objects no longer behaves as expected.
An industry-aware DevOps operating model makes those concerns part of the release itself. It combines the delivery automation already in Copado with reusable assets configured around the product, the customer s environments and the business process being changed.
The release is not complete when the metadata deploys. It is complete when the industry process still works. The release boundary has changedTraditional release planning often begins with a list of components and ends with a successful promotion. Industry-cloud delivery asks a broader set of questions:
- Which configuration and connected data must travel with the code
- In what order must dependent assets move
- What must be true in the target environment before promotion
- Which critical business journeys need regression coverage
- Which controls should change based on release type, risk or policy
These are not separate operational checks to be added at the end. They are part of the delivery design. The practical answer is an accelerator that packages three connected layers: data and configuration movement, release quality gates and Copado Robotic Testing (CRT) regression coverage.
The Industry DevOps operating model
Different industry processes. One connected release model.Care Programs, HCP Engagement, consent, participant management and patient-service journeys.
Revenue Lifecycle Management Product-to-order deliveryProduct, pricing, order and runtime configuration across the revenue lifecycle.
nCino Controlled banking changeBanking configuration, connected data movement and regression for critical workflows.
The model is consistent, but the implementation should not be generic. Each industry product brings its own release surface and its own definition of continuity.
Life Sciences Cloud: protect connected programs and journeysA Life Sciences Cloud change can touch Care Programs, HCP Engagement, consent, participant management, patient services, and product and order data. The delivery challenge is not simply moving each item. It is preserving the relationships that allow a regulated process to work as intended.
An accelerator for Life Sciences Cloud can package the relevant configuration and data, check for drift or conflict, confirm target deployability and run CRT coverage across Care Program enrollment, HCP engagement, consent and patient-service journeys. The release team sees the controls in the same flow as the promotion-not in a disconnected checklist.
Revenue Lifecycle Management: keep the lifecycle synchronizedRevenue Lifecycle Management connects product, pricing, order and runtime configuration. These elements form a dependency chain; treating them as unrelated deployment items creates avoidable uncertainty around sequencing and target readiness.
An industry-aware model packages the connected configuration, applies dependency and promotion gates, and tests the product-to-order journey after the change. That gives release leaders a clearer answer to the real question: did the revenue process remain coherent across configuration and runtime behavior
nCino: govern configuration and connected data togetherFor nCino, banking configuration and connected data must move under controlled promotion. A technically successful component deployment is only one part of that change.
The accelerator packages the relevant configuration and data, validates them before promotion, and applies CRT coverage to the banking workflows that matter after the release. The result is a repeatable control model that supports delivery speed without losing visibility into operational risk.
Three layers make the accelerator operational 1. Data and configuration packsThe first layer defines the assets that travel together. It captures the object relationships, configuration scope and required movement sequence for the industry process. Instead of rebuilding that knowledge for every release, the team has a reusable package that can be maintained as the implementation evolves.
2. Release quality gatesThe second layer turns release knowledge into executable control. Gates can assess dependencies, data movement, configuration integrity, target readiness and promotion policy at the relevant point in the path to production. This makes the control visible, repeatable and tied to the release record.
3. CRT regression coverageThe third layer validates the outcome at the level the business recognizes: the journey. The regression scope follows the affected process-Care Program enrollment, product-to-order, or a critical banking workflow-so the evidence says more than the deployment passed.
The operating principle
Move the connected assets, enforce the right control and verify the affected journey. The three layers work as one release model, not as independent tools or after-the-fact checks.
Reusable does not mean fixed. A useful industry accelerator is configured to the customer s object model, environments, release path and governance rules. It should make a clear distinction between what can be configured directly and what requires extension.
That distinction is essential because two customers on the same industry product may have different operating models, risk thresholds and release calendars. The value of the accelerator is the combination of proven delivery assets and a disciplined configuration process-not a claim that every implementation is identical.
Once configured, the model also needs an owner. Through Copado as a Service, CloudFulcrum can operate deployment execution, sandbox operations, asset and gate maintenance, CRT suite extension, release reporting and readiness for platform releases. The accelerator becomes part of the day-to-day release system rather than a one-time implementation artifact.
Start with one representative release problemThe fastest way to determine whether an industry accelerator is useful is to apply it to a real change. A focused working session should leave the team with a delivery blueprint it can evaluate, including:
- Industry object and configuration scope
- Quality gates mapped to policy and risk
- CRT scope for affected business journeys
- Deployment sequence and dependencies
- Direct configuration versus required extension
- An operating path after initial configuration
This moves the conversation from broad capability to release engineering. The customer can see where the accelerator fits, which assets are reusable and what must be adapted to the implementation.
Industry clouds deserve a release model built around the process they run. When data and configuration movement, quality gates and regression coverage are designed together, Copado becomes the foundation for a more complete and repeatable industry delivery system.
Bring one industry release problem.Leave with the delivery blueprint-covering the connected assets, release gates, CRT scope and deployment sequence for a representative change.
Book Your Accelerator Session About CloudFulcrum CloudFulcrum helps enterprises engineer and operate Salesforce delivery models that connect release automation, quality controls and business-process assurance. Learn more about CloudFulcrum s Salesforce DevOps capabilities . -->Position: Sr. DevOps Engineer
Client: Internal (DWP)
Location: Hyderabad (Hybrid)
This position requires a senior Devops person having very good skills in AWS.
Role at a glance
We need a DevOps / Platform Engineer to build and run one platform that ships three ways: AWS cloud, hybrid, and fully air-gapped on customer premises. The platform combines regulatory licensing, spectrum monitoring integration and AI-assisted analysis for national spectrum regulators.
Expected Tasks
- Kubernetes clusters. Build and operate k0s on customer servers, in single-node and three-node high-availability layouts, and Amazon EKS in the cloud.
- Air-gapped delivery. Package each release as a signed offline bundle holding images, Helm charts and configuration. Install and upgrade it at sites with no internet access.
- CI/CD migration. Move the existing pipeline from AWS CodeCommit, CodePipeline and Elastic Beanstalk to Git and pipelines on Azure DevOps Server (TFS), producing container images instead of Beanstalk packages.
- Containers and charts. Write production Dockerfiles (multi-stage, pinned base images, non-root) and Helm charts for about 18 workloads across TypeScript, Python and Go services.
- Data services. Run PostgreSQL through CloudNativePG (with PostGIS and pgvector), NATS JetStream and SeaweedFS. Support SQL Server Availability Groups where a customer mandates SQL Server.
- Availability and recovery. Design so that losing any one server causes no outage. Set up off-host backups, and run scheduled restore tests and failover drills.
- Observability. Operate OpenTelemetry, Prometheus, Loki, Tempo and Grafana, with alerts and dashboards for each deployment profile.
- Security and supply chain. Generate an SBOM for every release, scan images, sign them, and admit only signed images (Kyverno). Manage secrets and certificates (Vault or encrypted Kubernetes Secrets, cert-manager).
- Gateway and identity. Operate Kong as the API gateway and Keycloak for identity, and manage mTLS certificates for edge agents at monitoring sites.
- GPU nodes. Provision and maintain GPU servers for self-hosted model serving (vLLM).
- Environments. Run development, nightly high-availability test and staging environments; manage AWS infrastructure with Terraform.
- Runbooks and handover. Write install, upgrade and rollback runbooks for customer operations teams, and support installations through customer acceptance.
Must-have skills
Production Kubernetes and offline delivery matter most; the rest can be learned on the job.
- 5-8 years in DevOps, SRE or platform engineering, with at least 3 years running Kubernetes in production.
- Hands-on with an on-premises Kubernetes distribution (k0s, k3s, RKE2 or similar), not only managed cloud clusters.
- Helm chart authoring and multi-stage Docker builds for services in more than one language.
- CI/CD pipelines in Azure DevOps Server / TFS, Azure DevOps or GitLab CI, including build agents you run yourself.
- Delivering software into restricted or air-gapped networks: private registries, image mirroring, offline dependency bundles.
- Operating PostgreSQL in Kubernetes, including replication, failover, backup and point-in-time restore.
- Prometheus and Grafana, plus a log stack such as Loki or ELK.
- Strong Linux administration and networking: TLS, DNS, load balancing, firewalls, VPNs.
- Terraform for AWS (VPC, EKS, IAM, S3).
- Bash or Python scripting for automation.
- Clear written English for runbooks that a customers operations team can follow without you.
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
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Section · 02
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About Cloudfulcrum

Cloudfulcrum
Software Product
31
employees
2019
7 years old
Hyderabad / Secunderabad, Telangana
India
₹8.4L PA avg
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