DevOps Engineer Senior

Amura’s Vision 

We believe that the most under-appreciated route to releasing untapped human potential is to build a healthier body, and through which a better brain. This allows us to do more of everything that is important to each one of us.

Billions of healthier brains, sitting in healthier bodies, can take up more complex problems that defy solutions today, including many existential threats, and solve them in just a few decades.

Billions of healthier brains will make the world richer beyond what we can imagine today. The surplus wealth, combined with better human capabilities, will lead us to a new renaissance, giving us a richer and more beautiful culture.

These healthier brains will be equipped with deeper intellect, be less acrimonious, more magnanimous, and have a kinder outlook on the world, resulting in a world that is better than any previous time.

We find this vision of the future exhilarating. Our hopes and dreams are to create this future as quickly as possible and ensure that it is widely distributed and optimized to maximize all forms of human excellence. 

Role Overview 

We are looking for a highly skilled Senior DevOps Engineer (AI-Native Infrastructure & Platform Engineering) with deep expertise in AWS cloud infrastructure, automation, AI infrastructure operations, and modern DevOps/SRE practices.

This role goes beyond traditional DevOps and requires a seasoned specialist capable of building and operating AI-ready infrastructure platforms that support high-throughput APIs, LLM/AI workloads, GPU-based compute, data-intensive systems, real-time inference pipelines, and scalable ML platforms.

You will be responsible for architecting, automating, securing, and optimizing highly scalable and cost-efficient cloud environments that enable high-velocity engineering and AI teams. This is an ideal position for someone who combines technical ownership, an automation-first mindset, and a passion for developer productivity and platform reliability. 

Key Responsibilities 

Cloud Infrastructure & Platform Engineering (AWS) 

• Architect, deploy, and manage highly scalable and secure infrastructure on AWS. Design cloud platforms supporting AI/ML workloads, data pipelines, real-time APIs, and high-concurrency backend systems.
• Hands-on expertise with key AWS services including EC2, ECS/EKS, Lambda, RDS, DynamoDB, S3, VPC, CloudFront, IAM, CloudWatch, and GPU-enabled instances.
• Build and maintain Infrastructure-as-Code (IaC) using Terraform, CloudFormation, or AWS CDK.
• Design multi-AZ and multi-region architectures for high availability and disaster recovery (HA/DR).
• Build reusable platform templates and shared infrastructure modules. 

AI/ML Infrastructure & MLOps 

• Build and maintain infrastructure for LLM applications, AI inference workloads, model serving platforms, vector databases, and feature stores.
• Support GPU-based workloads and optimize compute/storage usage.
• Enable scalable deployment patterns for AI applications using Kubernetes/EKS. Collaborate with Data Science and ML Engineering teams on model deployment, training/tuning of models, CI/CD for ML systems, experiment environments, and reproducibility.
• Support orchestration and deployment of AI workflows and inference services while implementing observability and reliability for AI pipelines. 

CI/CD, Automation & Developer Productivity 

• Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline.
• Automate deployments, environment provisioning, and release workflows.
• Build self-service developer platforms, preview environments, and reusable deployment workflows to improve developer productivity.
• Implement automated patching, scaling, backups, cleanup workflows, and drift detection. 

Containers, Kubernetes & Platform Reliability

• Manage Docker-based environments, containerized applications, and optimize workloads using Kubernetes (EKS) or ECS/Fargate.
• Manage autoscaling, cluster health, node pools, ingress, service mesh, and workload isolation.
• Optimize infrastructure for performance, resilience, and cost-efficiency.
• Implement progressive deployment strategies including blue/green, canary, and rolling deployments. 

Observability, Incident Response & SRE Practices

• Implement observability stacks using CloudWatch, Prometheus, Grafana, ELK, Datadog, OpenTelemetry, or New Relic.
• Build actionable dashboards and intelligent alerting systems while defining and tracking SLIs, SLOs, and SLAs.
• Lead incident response, root cause analysis, and blameless postmortems to reduce operational toil and improve MTTR.

FinOps, Cost Governance & Security

• Continuously monitor and optimize cloud costs (compute utilization, storage lifecycle, GPU usage, and data transfer) using AWS Cost Explorer, Budgets, Trusted Advisor, CloudHealth, or Kubecost.
• Implement AWS security best practices for IAM, VPCs, security groups, NACLs, encryption, and manage secrets using KMS, SSM Parameter Store, or Vault.
• Build secure CI/CD pipelines with automated security checks, least-privilege access, audit logging, and ensure compliance readiness for ISO 27001, SOC2, and GDPR.

Collaboration, Leadership & Platform Culture

• Work closely with engineering, AI/ML, QA, product, and operations teams to drive a DevOps, SRE, GitOps, and automation-first culture.
• Mentor junior DevOps and Platform Engineers while creating and maintaining detailed runbooks, architecture diagrams, and platform documentation.

Skills & Qualifications

Must-Have:

• 7+ years of experience in DevOps, SRE, Platform Engineering, or Cloud Infrastructure Engineering.
• Strong expertise in AWS cloud architecture, services, and deep understanding of Kubernetes (EKS), containers, and cloud-native systems.
• Strong Infrastructure-as-Code expertise using Terraform, CloudFormation, or CDK. Strong Linux administration, networking, DNS, routing, and load balancing knowledge. Strong scripting/programming experience in Python, Bash, or Go (preferred). Experience with CI/CD automation, GitOps workflows, and observability platforms supporting scalable production systems.

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Here are answers to some questions you may have

Where is your office?

Chennai (Velachery)

Work Model

Work from Office – because great stories are built in person!

Do you have an online presence?

https://amura.ai (we are @AmuraHealth on all social media)

Job Details

- Job Title: Senior DevOps Engineer

- Industry: Consumer Internet, Technology & Travel and Tourism Platform

- Function - IT

- Experience Required: 4-7 years

- Employment Type: Full Time

- Job Location: Bengaluru

- CTC Range: Best in Industry

Criteria:

• Strong DevOps / Infrastructure Engineer Profiles.
• Must have 4+ years of hands-on experience working as a DevOps Engineer / Infrastructure Engineer / SRE / DevOps Consultant.
• Must have hands-on experience with Kubernetes and Docker, including deployment, scaling, or containerized application management.
• Must have experience with Infrastructure as Code (IaC) or configuration management tools such as Terraform, Ansible, Chef, or Puppet.
• Must have strong automation and scripting experience using Python, Go, Bash, Shell, or similar scripting languages.
• Must have working experience with distributed databases or data systems such as MongoDB, Redis, Cassandra, Elasticsearch, or Kafka.
• Candidate must demonstrate strong expertise in at least one of the following areas - Databases / Distributed Data Systems, Observability & Monitoring, CI/CD Pipelines. Networking Concepts, Kubernetes / Container Platforms
• Candidates must be from B2C Product-based companies only.
• (Education) – BE / B.Tech or equivalent

Preferred

• Experience working with microservices or event-driven architectures.
• Exposure to cloud infrastructure, monitoring, reliability, and scalability practices.
• (Skills) – Understanding of programming languages such as Go, Python, or Java.
• Preferred (Environment) – Experience working in high-scale production or fast-growing product startups.

Job Description 

As a DevOps Engineer, you will be working on building and operating infrastructure at scale, designing and implementing a variety of tools to enable product teams to build and deploy their services independently, improving observability across the board, and designing for security, resiliency, availability, and stability. If the prospect of ensuring system reliability at scale and exploring cutting-edge technology to solve problems, excites you, then this is your fit.

Job Responsibilities:

• Own end-to-end infrastructure right from non-prod to prod environment including self-managed DBs
• Codify our infrastructure
• Do what it takes to keep the uptime above 99.99%
• Understand the bigger picture and sail through the ambiguities
• Scale technology considering cost and observability and manage end-to-end processes
• Understand DevOps philosophy and evangelize the principles across the organization
• Strong communication and collaboration skills to break down the silos

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.

• Seeking an Individual carrying around 5+ yrs of experience.
• Must have skills - Jenkins, Groovy, Ansible, Shell Scripting, Python, Linux Admin
• Terraform, AWS deep knowledge to automate and provision EC2, EBS, SQL Server, cost optimization, CI/CD pipeline using Jenkins, Server less automation is plus.
• Excellent writing and communication skills in English. Enjoy writing crisp and understandable documentation
• Comfortable programming in one or more scripting languages
• Enjoys tinkering with tooling. Find easier ways to handle systems by doing some research. Strong awareness around build vs buy.

• Essentail Skills:
• Docker
• Jenkins
• Python dependency management using conda and pip

• Base Linux System Commands, Scripting
• Docker Container Build & Testing
• Common knowledge of minimizing container size and layers
• Inspecting containers for un-used / underutilized systems
• Multiple Linux OS support for virtual system

• Has experience as a user of jupyter / jupyter lab to test and fix usability issues in workbenches
• Templating out various configurations for different use cases (we use Python Jinja2 but are open to other languages / libraries)
• Jenkins PIpeline
• Github API Understanding to trigger builds, tags, releases
• Artifactory Experience
• Nice to have: Kubernetes, ArgoCD, other deployment automation tool sets (DevOps)

As DevOps Engineer, you are responsible to setup and maintain GIT repository, DevOps tools like Jenkins, UCD, Docker, Kubernetes, Jfrog Artifactory, Cloud monitoring tools, Cloud security.

• Setup, configure, and maintain GIT repos, Jenkins, UCD, etc. for multi hosting cloud environments.
• Architect and maintain the server infrastructure in AWS. Build highly resilient infrastructure following industry best practices.
• Working on Docker images and maintaining Kubernetes clusters.
• Develop and maintain the automation scripts using Ansible or other available tools.
• Maintain and monitor cloud Kubernetes Clusters and patching when necessary.
• Working on Cloud security tools to keep applications secured.
• Participate in software development lifecycle, specifically infra design, execution, and debugging required to achieve successful implementation of integrated solutions within the portfolio.
• Required Technical and Professional Expertise.
• Minimum 4-6 years of experience in IT industry.
• Expertise in implementing and managing Devops CI/CD pipeline.
• Experience in DevOps automation tools. And Very well versed with DevOps Frameworks, Agile.
• Working knowledge of scripting using shell, Python, Terraform, Ansible or puppet or chef.
• Experience and good understanding in any of Cloud like AWS, Azure, Google cloud.
• Knowledge of Docker and Kubernetes is required.
• Proficient in troubleshooting skills with proven abilities in resolving complex technical issues.
• Experience with working with ticketing tools.
• Middleware technologies knowledge or database knowledge is desirable.
• Experience and well versed with Jira tool is a plus.

Job Brief:

We are looking for candidates that have experience in development and have performed CI/CD based projects. Should have a good hands-on Jenkins Master-Slave architecture, used AWS native services like CodeCommit, CodeBuild, CodeDeploy and CodePipeline. Should have experience in setting up cross platform CI/CD pipelines which can be across different cloud platforms or on-premise and cloud platform.

Job Location:

Pune.

Job Description:

• Hands on with AWS (Amazon Web Services) Cloud with DevOps services and CloudFormation.
• Experience interacting with customer.
• Excellent communication.
• Hands-on in creating and managing Jenkins job, Groovy scripting.
• Experience in setting up Cloud Agnostic and Cloud Native CI/CD Pipelines.
• Experience in Maven.
• Experience in scripting languages like Bash, Powershell, Python.
• Experience in automation tools like Terraform, Ansible, Chef, Puppet.
• Excellent troubleshooting skills.
• Experience in Docker and Kuberneties with creating docker files.
• Hands on with version control systems like GitHub, Gitlab, TFS, BitBucket, etc.