Sr. DevOps Engineer

Location: Bangalore

Experience: 2–5 years

Type: Full-time | On-site

Open Roles: 1

Start: Immediate

Why this role exists

Most engineering teams choose between speed and stability.

We need both.

Today:

• Deployments carry risk
• Cloud costs are higher than they should be
• Compliance is reactive, not built-in

This role exists to build a platform where:

• We can deploy fast without breaking production
• We can scale without runaway cost
• We can pass enterprise InfoSec reviews without firefighting

What you’ll do

You will not just manage infrastructure.

You will build the platform that engineering runs on.

1. Drive cloud cost efficiency

• Reduce Azure compute spend by 40%
• Implement:
• Reserved Instances / savings plans
• Right-sizing of workloads
• Scheduling for non-critical workloads
• Continuously monitor and optimize cost vs performance

2. Build zero-downtime deployment systems

• Ship a deployment pipeline that supports:
• 5+ production deployments per week
• Zero customer-visible downtime
• Implement:
• Blue-green / canary deployments
• Automated health checks
• Safe rollout strategies

3. Enable fast and safe releases

• Reduce time-to-launch significantly
• Ensure:
• High reliability in every release
• Ability to rollback instantly if something breaks
• Create systems where:
• Scaling up is seamless when things go right
• Failures are contained when they don’t

4. Build disaster recovery and compliance readiness

• Create DR/BCP systems that pass enterprise audits from:
• HDFC Life, SBI Life
• Ensure:
• Backup and recovery processes are defined and tested
• Failover strategies are documented and executable
• Build compliance as part of the system, not an afterthought

5. Embed security into the pipeline

• Integrate:
• SAST (Static Application Security Testing)
• DAST (Dynamic Application Security Testing)
• SCA (Software Composition Analysis)
• Secret scanning
• Container scanning
• IaC scanning
• Ensure vulnerabilities are caught before deployment

6. Enforce policy-as-code

• Implement:
• OPA / Gatekeeper
• Azure Policy
• Prevent non-compliant infrastructure from being deployed
• Ensure consistency across environments

7. Build a scalable platform layer

• Create systems that:
• Support increasing deployment frequency
• Maintain reliability under scale
• Work closely with backend and SRE teams to:
• Improve system stability
• Reduce operational overhead

What success looks like

• Cloud costs reduce by ≥ 40%
• Deployments are:
• Frequent
• Safe
• Invisible to customers
• Rollbacks are instant and reliable
• DR/BCP passes enterprise audits in the first attempt
• Security is embedded in the pipeline, not patched later
• Engineering teams ship faster with confidence

Who you are

• You have 2-5 years of experience in DevOps / Platform Engineering
• You have worked with:
• Cloud platforms (Azure preferred)
• CI/CD systems
• Infrastructure as Code
• You think in:
• Systems
• Trade-offs (speed vs reliability vs cost)
• You are comfortable owning:
• Production infrastructure
• Deployment systems

What will make you stand out

• Experience with:
• High-frequency deployment systems
• Cost optimization at scale
• Security-first pipelines
• Strong understanding of:
• Kubernetes / container orchestration
• Monitoring and observability
• Distributed system reliability
• Experience passing enterprise security/compliance audits

Why join

• You will define how engineering ships and scales
• Your work directly impacts:
• Reliability
• Cost
• Deployment velocity
• You will build a platform that moves from:
• Fragile → predictable and scalable

What this role is not

• Not manual infra management
• Not reactive firefighting
• Not limited to CI/CD maintenance

What this role is

• A builder of deployment systems
• A driver of cost efficiency
• A guardian of reliability and compliance

One question to self-evaluate

Can you build a platform where we deploy faster, spend less, and never break production?

Role: Full-Time, Long-Term Required: Docker, GCP, CI/CD Preferred: Experience with ML pipelines

OVERVIEW

We are seeking a DevOps engineer to join as a core member of our technical team. This is a long-term position for someone who wants to own infrastructure and deployment for a production machine learning system. You will ensure our prediction pipeline runs reliably, deploys smoothly, and scales as needed.

The ideal candidate thinks about failure modes obsessively, automates everything possible, and builds systems that run without constant attention.

CORE TECHNICAL REQUIREMENTS

Docker (Required): Deep experience with containerization. Efficient Dockerfiles, layer caching, multi-stage builds, debugging container issues. Experience with Docker Compose for local development.

Google Cloud Platform (Required): Strong GCP experience: Cloud Run for serverless containers, Compute Engine for VMs, Artifact Registry for images, Cloud Storage, IAM. You can navigate the console but prefer scripting everything.

CI/CD (Required): Build and maintain deployment pipelines. GitHub Actions required. You automate testing, building, pushing, and deploying. You understand the difference between continuous integration and continuous deployment.

Linux Administration (Required): Comfortable on the command line. SSH, diagnose problems, manage services, read logs, fix things. Bash scripting is second nature.

PostgreSQL (Required): Database administration basics—backups, monitoring, connection management, basic performance tuning. Not a DBA, but comfortable keeping a production database healthy.

Infrastructure as Code (Preferred): Terraform, Pulumi, or similar. Infrastructure should be versioned, reviewed, and reproducible—not clicked together in a console.

WHAT YOU WILL OWN

Deployment Pipeline: Maintaining and improving deployment scripts and CI/CD workflows. Code moves from commit to production reliably with appropriate testing gates.

Cloud Run Services: Managing deployments for model fitting, data cleansing, and signal discovery services. Monitor health, optimize cold starts, handle scaling.

VM Infrastructure: PostgreSQL and Streamlit on GCP VMs. Instance management, updates, backups, security.

Container Registry: Managing images in GitHub Container Registry and Google Artifact Registry. Cleanup policies, versioning, access control.

Monitoring and Alerting: Building observability. Logging, metrics, health checks, alerting. Know when things break before users tell us.

Environment Management: Configuration across local and production. Secrets management. Environment parity where it matters.

WHAT SUCCESS LOOKS LIKE

Deployments are boring—no drama, no surprises. Systems recover automatically from transient failures. Engineers deploy with confidence. Infrastructure changes are versioned and reproducible. Costs are reasonable and resources scale appropriately.

ENGINEERING STANDARDS

Automation First: If you do something twice, automate it. Manual processes are bugs waiting to happen.

Documentation: Runbooks, architecture diagrams, deployment guides. The next person can understand and operate the system.

Security Mindset: Secrets never in code. Least-privilege access. You think about attack surfaces.

Reliability Focus: Design for failure. Backups are tested. Recovery procedures exist and work.

CURRENT ENVIRONMENT

GCP (Cloud Run, Compute Engine, Artifact Registry, Cloud Storage), Docker, Docker Compose, GitHub Actions, PostgreSQL 16, Bash deployment scripts with Python wrapper.

WHAT WE ARE LOOKING FOR

Ownership Mentality: You see a problem, you fix it. You do not wait for assignment.

Calm Under Pressure: When production breaks, you diagnose methodically.

Communication: You explain infrastructure decisions to non-infrastructure people. You document what you build.

Long-Term Thinking: You build systems maintained for years, not quick fixes creating tech debt.

EDUCATION

University degree in Computer Science, Engineering, or related field preferred. Equivalent demonstrated expertise also considered.

TO APPLY

Include: (1) CV/resume, (2) Brief description of infrastructure you built or maintained, (3) Links to relevant work if available, (4) Availability and timezone.

About Company:

• Role Overview

• Senior Engineer with a strong background and experience in cloud related technologies and architectures. Can design target cloud architectures to transform existing architectures together with the in-house team. Can actively hands-on configure and build cloud architectures and guide others.

• Key Knowledge

• 3-5+ years of experience in AWS/GCP or Azure technologies
• Is likely certified on one or more of the major cloud platforms
• Strong experience from hands-on work with technologies such as Terraform, K8S, Docker and orchestration of containers.
• Ability to guide and lead internal agile teams on cloud technology
• Background from the financial services industry or similar critical operational experience

Please find the JD below: 

• Candidate should have good Platform experience on Azure with Terraform. 
• The devops engineer needs to help developers, create the Pipelines and K8s Deployment Manifests. 
• Good to have experience on migrating data from (AWS) to Azure. 

• To manage/automate infrastructure automatically using Terraforms. Jenkins is the key CI/CD tool which we uses and it will be used to run these Terraforms. 
• VMs to be provisioned on Azure Cloud and managed. 
• Good hands-on experience of Networking on Cloud is required. 
• Ability to setup Database on VM as well as managed DB and Proper set up of cloud hosted microservices needs to be done to communicate with the db services. 
• Kubernetes, Storage, KeyValult, Networking (load balancing and routing) and VMs are the key infrastructure expertise which are essential. 

• Requirement is to administer Kubernetes cluster end to end. (Application deployment, managing namespaces, load balancing, policy setup, using blue green/canary deployment models etc). 
• The experience in AWS is desirable. 
• Python experience is optional however Power shell is mandatory. 
• Know-how on the use of GitHub 
• Administration of Azure Kubernetes services 

About BootLabs

https://www.google.com/url?q=https://www.bootlabs.in/&;sa=D&source=calendar&ust=1667803146567128&usg=AOvVaw1r5g0R_vYM07k6qpoNvvh6" target="_blank">https://www.bootlabs.in/

-We are a Boutique Tech Consulting partner, specializing in Cloud Native Solutions. 
-We are obsessed with anything “CLOUD”. Our goal is to seamlessly automate the development lifecycle, and modernize infrastructure and its associated applications.
-With a product mindset, we enable start-ups and enterprises on the cloud
transformation, cloud migration, end-to-end automation and managed cloud services. 
-We are eager to research, discover, automate, adapt, empower and deliver quality solutions on time.
-We are passionate about customer success. With the right blend of experience and exuberant youth in our in-house team, we have significantly impacted customers.

• AWS 

•  Azure

• GCP

• Development and maintenance of Continuous Integration System on JENKINS.
• Build management for the planned major/minor releases
• Release process management and maintenance
• Enhancement and development of build/release system features.
  
  

Required Qualifications:

• 2 - 3 years relevant work experience in Jenkins / Scripting / C / Linux
• Expertise in scripting languages like a shell, python, etc
• Work experience in handling Make/CMake build systems
• Expertise in GIT source revision control
• Experience with Yocto build systems and recipes

• Health Memberships 
• Sports Subscriptions 
• Entertainment Subscriptions 
• Key Conferences and Event Passes
• Learning Stipend 
• Team Lunches and Parties 
• Travel Reimbursements 
• ESOPs