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DevOps Engineer
DevOps Engineer

DevOps Engineer at Talent Pro · Bengaluru (Bangalore) · 4 - 7 years · ₹20L - ₹25L / yr · Bootstrapped · Posted 7 Aug 2025

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DevOps Engineer

Mayank choudhary's profile picture
Posted by Mayank choudhary
4 - 7 yrs
₹20L - ₹25L / yr
Bengaluru (Bangalore)
Skills
Need candidate having 4–7 years of total experience, with a...
  • Need candidate having 4–7 years of total experience, with a minimum of 4 years in a full-time DevOps role.
  • Candidate should have Hands-on experience with major cloud platforms (GCP, AWS, Azure, OCI), more than one will be a plus.
  • Candidate should have Scripting skills in Python and shell scripting
  • Candidate should have Solid understanding of CI/CD concepts.
  • Candidate should be Proficient in Kubernetes


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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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About Talent Pro

Founded :
2024
Type :
Services
Size
Stage :
Bootstrapped

About

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Job Summary :

We are looking for a proactive and skilled DevOps Engineer to join our team and play a key role in building, managing, and scaling infrastructure for high-performance systems. The ideal candidate will have hands-on experience with Kubernetes, Docker, Python scripting, cloud platforms, and DevOps practices around CI/CD, monitoring, and incident response.

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Pre-requisite skills required for a DevOps Engineer role include:


  • 6+yrs exp in DevOps
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Strong experience with GitLab, TeamCity, Terraform, Kubernetes and Docker

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Advanced scripting skills in bash and PowerShell

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Company Overview:


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Responsibilities


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  • Apply AI-assisted engineering tools (e.g., GitHub Copilot, Claude Code) to speed up IaC authoring, pipeline debugging, and day-to-day scripting.


Qualifications

Must-Have Skills


  • Experience: 4–6 years of experience in DevOps, SRE, or Infrastructure Engineering.
  • OS: Linux & Windows administration (systemd, package management, log analysis).
  • Cloud: AWS (Active Directory, ECS, EC2, CloudFront, S3, VPC, IAM, RDS, Lambda basics).
  • Source Control: Git — branching, merge/rebase, PR reviews.
  • CI/CD (Jenkins): Pipeline creation and basic Groovy scripting.
  • Containerization (Docker + ECS): Task definitions, services, and clusters.
  • IaC: Terraform.
  • Monitoring: New Relic.
  • Scripting: Bash and Python scripting for automation.
  • Networking Basics: DNS, load balancers, security groups, VPNs.
  • Logging: ELK stack / CloudWatch Logs.
  • Database: MSSQL administration — backups, restores, basic performance troubleshooting.
  • Infrastructure Automation: Hands-on experience automating infrastructure provisioning, configuration, and deployment end-to-end.
  • AI-Assisted Engineering: Comfortable working with AI coding/DevOps assistants (e.g., GitHub Copilot, Claude Code) for IaC generation, scripting, and troubleshooting — verified via a mandatory AI proficiency assessment during interviews.


Nice-to-Have Skills

•     Configuration Management: Ansible.

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•     Other CI/CD Tools: GitHub Actions.

•     AWS cost optimization / FinOps awareness.

•     Datadog, CloudWatch, or Prometheus/Grafana.

•     AIOps: Exposure to AI-driven anomaly detection, root-cause analysis, or incident triage (e.g., Dynatrace Davis AI, Datadog Bits AI, Harness AIDA).

•     Database Basics: RDS backups, restores, performance tuning.

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AWS / Kubernetes / OpenShift / Linux –

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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)


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aarushi Mahajan
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Job Description:

  • Infrastructure Management: Design, implement, and manage scalable, reliable, and secure cloud infrastructure using AWS, GCP, and/or Azure.
  • CI/CD Pipelines: Develop and maintain continuous integration and continuous deployment (CI/CD) pipelines to streamline the development lifecycle.
  • Automation: Automate infrastructure provisioning, configuration management, and application deployment processes.
  • Monitoring and Performance: Implement monitoring, logging, and alerting solutions to ensure system health, performance, and reliability.
  • Security: Ensure the security of cloud infrastructure and applications, including identity management and compliance with industry standards.
  • Collaboration: Work closely with client and development teams to integrate DevOps practices and deliver high-quality software.
  • Documentation: Maintain comprehensive documentation of infrastructure, configurations, and processes.
  • Innovation: Stay current with emerging technologies and industry trends, integrating them into the DevOps strategy as appropriate.


Qualifications: 

  • Education: Bachelor's degree in Computer Science, Information Technology, or a related field.
  • Experience: 7 - 10 years of overall experience with relevant experience of at least 7 years in DevOps and served as a lead or senior engineer.
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Silfa Rodrigues
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HSR Bangalore
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 The Role 

As a **DevOps Engineer** you'll own the infrastructure and delivery backbone that 

keeps our platform running as we grow. You'll build the CI/CD, cloud infrastructure, and 

observability that let a small, fast-moving team ship confidently — and you'll keep our AI and 

data workloads reliable and affordable at scale. 

This is a hands-on role with real ownership: you won't be maintaining someone else's setup, 

you'll be shaping ours. You'll work closely with the backend, AI/ML, and data teams to make 

deployment boring, incidents rare, and scaling a non-event. --- 


What You'll Own 

**CI/CD & developer experience** 

- Build and maintain fast, reliable CI/CD pipelines so engineers ship multiple times a day with 

confidence. - Make the path from commit to production simple, safe, and repeatable, with sensible 

automated testing, rollbacks, and release controls. 

**Cloud infrastructure & IaC** - Own our cloud infrastructure (AWS/GCP) end to end, managed as code (Terraform or 

similar) — no click-ops. - Design for scale and cost-efficiency as store and conversation volumes grow. 

**Containers & orchestration** - Run our services on containers/Kubernetes: deployments, autoscaling, networking, and 

resource management. - Support the specific needs of AI/ML workloads, including GPU-backed inference and batch 

processing for the speech pipeline. 

**Reliability & observability (SRE)** - Own uptime, performance, and incident response — monitoring, logging, tracing, alerting, 

on-call, and blameless postmortems. - Define and defend SLOs; keep the platform dependable as it scales across clients. 

**Data & pipeline infrastructure** - Support the infrastructure behind large-scale, edge-to-cloud data movement and 

processing (audio ingestion, ASR/AI pipelines, analytics). - Keep data workloads reliable, performant, and cost-aware. 

**Security & compliance** - Bake security into the platform: secrets management, IAM/least-privilege, encryption in 

transit and at rest, network hardening, and vulnerability management. - Support compliance readiness (including India's DPDP Act and enterprise-client security 

requirements) for a product that handles sensitive customer conversations. 

**Cost & scale** - Own cloud cost visibility and optimization; make scaling decisions that balance reliability 

and spend. --- 


What You'll Bring - 6+ years in DevOps, SRE, platform, or infrastructure engineering, running production 

systems at meaningful scale. - Strong hands-on experience with a major cloud provider (**AWS or Azure or GCP**) and 

Infrastructure-as-Code (**Terraform** or equivalent). - Solid experience with **containers and Kubernetes** in production. - Experience building and owning **CI/CD** pipelines (e.g. GitHub Actions, GitLab CI, 

Jenkins, Argo, or similar). 

- Comfort with a scripting/automation language (Python, Go, or Bash) and a strong 

automation-first mindset. - Real experience with **observability** (Prometheus/Grafana, ELK, Datadog, 

OpenTelemetry, or similar) and running incident response / on-call. - A security-conscious approach — secrets, IAM, encryption, and least-privilege as defaults. - Startup temperament: ownership, pragmatism, and a bias to automate and ship. - Based in or willing to relocate to Bangalore, and up for an onsite/hybrid, in-person team. 


Bonus Points - Experience running **ML/AI or GPU workloads** in production (inference serving, batch 

pipelines, model deployment). - Experience with data-intensive infrastructure — streaming/queues (Kafka, SQS), data 

pipelines, or large object/audio storage. - Exposure to **edge devices / IoT fleets**, OTA updates, or high-volume device-to-cloud 

ingestion. - Experience with compliance/security frameworks (SOC 2, ISO 27001, DPDP). - FinOps / cloud cost-optimization experience. - Early-stage startup experience. --- 


Why Join - Own infrastructure that's already live with leading retail brands and growing fast — real 

scale, real impact. - Work across genuinely interesting workloads: speech AI, GPU inference, large-scale data, 

and edge-to-cloud ingestion. - Small team, high ownership, direct line to engineering leadership — your decisions ship. - Build the platform foundation of a category-defining product from an

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Shubham Vishwakarma's profile image

Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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