DevOps Engineer

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.

Job Title: Cloud Engineer - Azure DevOps

Job Location: Mumbai (Andheri East)

About the company:
MIRACLE HUB CLIENT,   is a predictive analytics and artificial intelligence company headquartered in Boston, US with offices across the globe. We build prediction models and algorithms to solve high priority business problems. Working across multiple industries, we have designed and developed breakthrough analytic products and decision-making tools by leveraging predictive analytics, AI, machine learning, and deep domain expertise

Skill-sets Required:

• Azure Architecture
• DevOps Expert
• Infrastructure as a code
• Automate CICD pipelines
• Security and Risk Compliance
• Validate Tech Design

Job Role:

• Create a well-informed cloud strategy and manage the adaption process and Azure based architecture
• Develop and organize automated cloud systems
• Work with other teams in continuous integration and continuous deployment pipeline in delivering solutions
• Work closely with IT security to monitor the company's cloud privacy

Desired Candidate Profile:

• Bachelor’s degree in computer science, computer engineering, or relevant field.
• A minimum of 3 years’ experience in a similar role.
• Strong knowledge of database structure systems and data mining.
• Excellent organizational and analytical abilities.
• Outstanding problem solver.
• IMMEDIATE JOINING (A notice period of 1 month is also acceptable)
• Excellent English communication and presentation skills, both verbal and written
• Charismatic, competitive and enthusiastic personality with negotiation skills

Compensation: 12-15 LPA with minimum 5 years of experience. ( OR AS PER LAST DRAWN )

• Work towards improving the following 4 verticals - scalability, availability, security, and cost, for company's workflows and products.
• Help in provisioning, managing, optimizing cloud infrastructure in AWS (IAM, EC2, RDS, CloudFront, S3, ECS, Lambda, ELK etc.)
• Work with the development teams to design scalable, robust systems using cloud architecture for both 0-to-1 and 1-to-100 products.
• Drive technical initiatives and architectural service improvements.
• Be able to predict problems and implement solutions that detect and prevent outages.
• Mentor/manage a team of engineers.
• Design solutions with failure scenarios in mind to ensure reliability.
• Document rigorously to keep track of all changes/upgrades to the infrastructure and as well share knowledge with the rest of the team
• Identify vulnerabilities during development with actionable information to empower developers to remediate vulnerabilities
• Automate the build and testing processes to consistently integrate code
• Manage changes to documents, software, images, large web sites, and other collections of code, configuration, and metadata among disparate teams

• Proficient in Linux Commands line and troubleshooting.
• Proficient in AWS Services. Deployment, Monitoring and troubleshooting applications in AWS.
• Hands-on experience with CI tooling preferably with Jenkins.
• Proficient in deployment using Ansible.
• Knowledge of infrastructure management tools (Infrastructure as cloud) such as terraform, AWS cloudformation etc.
• Proficient in deployment of applications behind load balancers and proxy servers such as nginx, apache.
• Scripting languages: Bash, Python, Groovy.
• Experience with Logging, Monitoring, and Alerting tools like ELK(Elastic-search, Logstash, Kibana), Nagios. Graylog, splunk Prometheus, Grafana is a plus.