Platform Engineering / DevOps / Cloud Infrastructure Engineering

Hiring for Senior Devops Engineer - AWS

Exp : 6 - 8 yrs

Edu : BE/B.Tech

Work Location : Pune WFO

Notice Period : Immediate - 15 days

Skills :

5+ years of hands-on experience in DevOps Engineering and Infrastructure Management.

Exp with AWS Cloud, including EC2, S3, VPC, EKS, Lambda, IAM, CloudWatch, and other core AWS services.

Exp in Terraform for Infrastructure as Code (IaC).

Exp with Kubernetes (EKS) and Helm for container orchestration and deployment.

Good knowledge of Monitoring & Observability tools such as Grafana and Prometheus.

Job Summary

We are looking for an experienced Azure Cloud / DevOps Engineer with strong hands-on expertise in Azure PaaS services, Azure Kubernetes Service (AKS), and Azure DevOps. The candidate will be responsible for designing, implementing, deploying, and supporting highly available and scalable cloud applications and infrastructure on Microsoft Azure.

The ideal candidate should have strong experience in CI/CD, containerization, Kubernetes, Infrastructure as Code, Azure networking, security, monitoring, and automation.

Key Responsibilities

• Design, deploy, and manage Azure PaaS services including App Services, Azure Functions, Azure Storage, Azure SQL, Key Vault, Service Bus, Event Grid, and related services.
• Design, configure, and administer Azure Kubernetes Service (AKS) clusters.
• Manage Kubernetes workloads, deployments, services, ingress, namespaces, secrets, config maps, and autoscaling.
• Implement and maintain CI/CD pipelines using Azure DevOps.
• Develop and maintain build and release pipelines for application and infrastructure deployments.
• Implement Infrastructure as Code (IaC) using Terraform and/or ARM/Bicep templates.
• Build and manage Docker containers and container registries using Azure Container Registry (ACR).
• Implement deployment strategies such as rolling, blue-green, and canary deployments where required.
• Configure Azure networking components such as VNets, subnets, NSGs, private endpoints, load balancers, Application Gateway, and Azure DNS.
• Implement Azure security best practices including Managed Identity, RBAC, Key Vault, secrets management, and network security.
• Configure monitoring, logging, alerting, and troubleshooting using Azure Monitor, Log Analytics, Application Insights, and Container Insights.
• Automate infrastructure and operational activities using PowerShell, Azure CLI, Bash, or Python.
• Troubleshoot application, container, Kubernetes, pipeline, networking, and Azure infrastructure issues.
• Work closely with development, architecture, security, and operations teams to deliver reliable cloud solutions.
• Participate in production deployments, incident management, root-cause analysis, and performance optimization.

Required Skills

Azure

• Strong hands-on experience with Microsoft Azure.
• Azure PaaS services such as:
• Azure App Service
• Azure Functions
• Azure Storage
• Azure SQL
• Azure Key Vault
• Azure Service Bus
• Azure Event Grid
• Azure API Management
• Good understanding of Azure networking, IAM/RBAC, security, and governance.

AKS / Kubernetes

• Strong hands-on experience with AKS.
• Kubernetes architecture and administration.
• Deployments, Services, Ingress, ConfigMaps, Secrets, Namespaces.
• Helm and Kubernetes manifests.
• Horizontal Pod Autoscaler and cluster autoscaling.
• Container troubleshooting and performance

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)

Mactores is the agent-native AWS modernization firm. Most modernization work doesn't ship, it stalls in pilots, slips a year, or lands at three times the budget. We exist to ship it: production systems running, legacy retired, outcomes measured. Our delivery is built on Aedeon, the agent platform built by Mactores' founders' sister company, which absorbs the repetitive 60–70% of engagement work, discovery, dependency mapping, validation, test generation, that traditional consulting bills human hours against. Forward-deployed engineers own the rest: architecture, judgment, and cutover, on dates we commit to in the contract.

Legacy infrastructure doesn't retire itself. Someone has to build the pipelines, rehearse the cutover, and carry the release into production  and that's this seat. As a Senior AWS DevOps Engineer, you serve our application and infrastructure modernization work: you own build and release cycles for customer projects, land migrations from legacy hardware to AWS, and make deployments boring in the best sense of the word.

Agents change what this job looks like day to day. Aedeon and automation handle the repetitive discovery, mapping, and validation work that used to eat engineer hours. That leaves you the parts that actually need a senior engineer: infrastructure architecture, risk tradeoffs, release judgment, and the operational standards the whole team ships against. You'll work client-facing, embedded with customer teams, and the delivery commitment is one you carry personally.

What we are looking for?

• 4+ years with Terraform for Infrastructure as Code (IaC) including modules, remote state, state management, imports and multi account providers.
• Experience in designing highly available and secure AWS architecture within strong understanding of RTO/RPO and DR Strategies.
• 4+ years in configuration management and systems engineering, supporting large-scale Agile environments.
• 4+ years of Linux or Windows administration.
• 4+ years working with Git, with a solid grasp of branching and merging strategies.
• 4+ years hands-on with AWS infrastructure and platform services.
• 2+ years with cloud automation tools such as Ansible or Chef.
• 2+ years with container orchestration, Kubernetes (EKS), AWS ECS, and Docker.
• A proactive, solutions-oriented approach and a drive to improve reliability and scalability.

What you will do?

• Automate infrastructure creation with Terraform and AWS CloudFormation — infrastructure as code, not tickets and toil.
• Own application configuration management and drive Infrastructure as Code through deployment tooling.
• Own the build and release cycle for customer projects, end to end.
• Share responsibility for deploying releases and for operations and maintenance work.
• Improve the operations infrastructure we ship with — Jenkins clusters, Bitbucket, monitoring tools (Consul), and metrics tools like Graphite and Grafana.
• Support the engineering team operationally and help migrate legacy infrastructure to the cloud — retiring the old systems, not just standing up new ones.
• Establish and enforce operational best practices, and hold releases to them.
• Help hire culturally aligned engineers and mentor them as they grow.
• Work with the founders on team strategy and long-term technical planning.
• Work across distributed teams in the US and India, and with customer SMEs, to keep the business logic honest through migration.

Role: Azure DevOps AI Architect

Location: Bangalore (Onsite)

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.

• 10+ years of experience in cloud engineering and architecture.

• 5+ years of hands-on experience with Microsoft Azure across computer, networking, storage, identity, and data services.

• Proven experience designing and implementing enterprise-grade CI/CD pipelines.

• Strong hands-on expertise with Infrastructure-As-Code (Terraform, Bicep, or ARM).

• Demonstrated experience architecting and deploying AI/ML solutions on Azure (Azure OpenAI, Azure ML, AI Foundry).

• Deep knowledge of DevSecOps principles, tools, and practices. • Experience with containerization and orchestration: Docker, Kubernetes (AKS).

• Proficiency in scripting and development: Python, PowerShell, Bash.

• Excellent communication and stakeholder management skills.

Preferred Qualifications

• Microsoft Certified: Azure Solutions Architect Expert.

• Microsoft Certified: DevOps Engineer Expert.

• Microsoft Certified: Azure AI Engineer Associate.

• Experience with Azure API Management (APIM), Event Grid, and Azure Functions.

• Familiarity with Datadog, Prometheus, or equivalent observability platforms.

• Experience in the real estate, retail, or enterprise industry sector.

• Knowledge of agentic AI frameworks and LLM orchestration patterns (LangChain, Semantic Kernel, MCP).

• Background in building Internal Developer Platforms (IDP).

We are seeking a highly experienced Azure AI, AIOps & MLOps Architect to lead enterprise-scale AI platform engineering, cloud modernization, DevSecOps transformation, and intelligent automation initiatives.

The ideal candidate should possess deep expertise in Microsoft Azure, Azure AI Foundry, Azure OpenAI, Azure Machine Learning, Kubernetes, Terraform, Azure DevOps, and enterprise observability platforms. The role will focus on designing scalable AI platforms, implementing MLOps and AIOps capabilities, enabling Agentic AI architectures, and driving cloud-native engineering practices across the organization.

Key Responsibilities

Cloud Architecture & Engineering

•     Design and implement scalable, secure, and highly available solutions on Microsoft Azure.

•     Define cloud architecture standards, reference architectures, and best practices.

•     Lead cloud migration and modernisation initiatives across enterprise workloads.

•     Implement multi-region disaster recovery and business continuity strategies.

•     Oversee Azure networking, identity, security, and governance frameworks.

DevOps & CI/CD

•     Architect and implement end-to-end CI/CD pipelines using Azure DevOps or GitHub Actions.

•     Drive DevSecOps culture — embedding security scanning, quality gates, and compliance into the delivery pipeline.

•     Champion Infrastructure-as-Code (IaC) practices using Terraform, Bicep, or ARM templates.

•     Establish branching strategies, release management, and environment promotion standards.

•     Define and enforce platform engineering standards and internal developer tooling.

AI & Machine Learning Integration

•     Architect AI/ML solutions leveraging Azure AI services — Azure OpenAI, Azure Machine Learning, Azure AI Foundry, and Cognitive Services.

•     Design intelligent automation and agentic workflows integrated into enterprise DevOps processes.

•     Implement AI-powered capabilities such as code review assistance, anomaly detection, predictive analytics, and natural language automation.

•     Define AI governance frameworks: model evaluation, prompt management, responsible AI, and cost controls.

•     Design and implement enterprise MLOps frameworks.

•     Build automated model training, validation, deployment, and monitoring pipelines.

•     Establish model governance and lifecycle management.

Generative AI & Agentic AI

• Design enterprise GenAI solutions using Azure OpenAI.
• Build AI Agents using Azure AI Foundry.
• Develop Agent-to-Agent communication patterns.
• Implement Retrieval Augmented Generation (RAG) architectures.
• Build enterprise Knowledge Management and AI Skill Registry platforms.
• Design multi-agent orchestration frameworks.

Leadership & Stakeholder Engagement

•     Serve as the technical authority and subject matter expert for Azure AI and DevOps practices.

•     Mentor and guide junior architects, developers, and DevOps engineers.

•     Collaborate with business stakeholders, product owners, and vendors to translate requirements into technical solutions.

•     Produce architecture documentation, decision records (ADRs), and roadmaps.

•     Represent the technology function in enterprise architecture forums and governance boards.

Required Qualifications

•     Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.

•     10+ years of experience in cloud engineering and architecture.

•     5+ years of hands-on experience with Microsoft Azure across compute, networking, storage, identity, and data services.

•     Proven experience designing and implementing enterprise-grade CI/CD pipelines.

•     Strong hands-on expertise with Infrastructure-as-Code (Terraform, Bicep, or ARM).

•     Demonstrated experience architecting and deploying AI/ML solutions on Azure (Azure OpenAI, Azure ML, AI Foundry).

•     Deep knowledge of DevSecOps principles, tools, and practices.

•     Experience with containerisation and orchestration: Docker, Kubernetes (AKS).

•     Proficiency in scripting and development: Python, PowerShell, Bash.

•     Excellent communication and stakeholder management skills.

Preferred Qualifications

•     Microsoft Certified: Azure Solutions Architect Expert.

•     Microsoft Certified: DevOps Engineer Expert.

•     Microsoft Certified: Azure AI Engineer Associate.

•     Experience with Azure API Management (APIM), Event Grid, and Azure Functions.

•     Familiarity with Datadog, Prometheus, or equivalent observability platforms.

•     Experience in the real estate, retail, or enterprise industry sector.

•     Knowledge of agentic AI frameworks and LLM orchestration patterns (LangChain, Semantic Kernel, MCP).

•     Background in building Internal Developer Platforms (IDP).

Technical Skills

Domain

Technologies / Tools

Cloud Platform

Microsoft Azure (UAE North / Global)

DevOps & CI/CD

Azure DevOps, GitHub Actions, Jenkins

IaC

Terraform, Bicep, ARM Templates

AI / ML

Azure OpenAI, Azure AI Foundry, Azure ML, Cognitive Services

Containers

Docker, Kubernetes (AKS), Azure Container Apps

Identity & Security

Microsoft Entra ID, Azure Policy, Defender for Cloud

Observability

Datadog, Azure Monitor, Log Analytics, Application Insights

Databases

Azure SQL, PostgreSQL, Cosmos DB

Languages

Python, PowerShell, Bash, YAML

Why this role exists

Our infrastructure footprint is growing faster than our headcount, and we believe most of that

gap should be closed by automation and AI agents — not by hiring more humans to do toil. We

need someone early in their career who treats manual work as a bug, ships scripts and agents

instead of tickets, and wants to grow into deeper ownership over the next two years.

You will not be the most senior person on the team. You will be the one who multiplies the team.

What you'll own

In your first 1 months

• Take ownership of one slice of our CI/CD pipeline and make it measurably

faster, more reliable, or cheaper. We expect a number on a dashboard to move.

• Build at least three internal automations that replace manual ops toil —

using AI agents (Claude Code, agentic CLIs, scripted LLM workflows) as your force

multiplier.

• Be the first responder for a defined set of alerts. Write the runbooks. Drive

the alert volume down.

• Support senior engineers on AI/ML infrastructure (GPU nodes, inference

services, model deployment) — observe, document, and gradually take on contained

changes under review.

By 3 months you should be

• The go-to person for at least two production systems.

• Shipping routine infrastructure changes without needing senior review.

• Treating "manual" as a code smell.

Required (we will reject without these)

• 0–3 years hands-on experience with one major cloud (AWS, GCP, or

Azure — one is fine, depth beats breadth).

• Fluent in Linux command line, bash, and at least one scripting language

(Python or Go preferred).

• Have shipped something to production that real users hit. A side project

counts; a graded coursework lab does not.

• Comfortable with Docker — you can explain what an image vs. a

container is and why it matters.

• Working knowledge of networking fundamentals: DNS, HTTP/HTTPS,

TLS, ports, basic subnets — enough to debug "it works on my machine."

• Git fluency: branches, merges, rebases, conflict resolution.

• CI/CD pipelines — you have authored or substantially modified pipelines

in GitHub Actions, GitLab CI, ArgoCD, Jenkins, or similar. Not just "I clicked Re-run."

• Kubernetes basics — kubectl for real work, can read pod logs,

understand deployments and services, can debug a CrashLoopBackOff without

panicking. You do not need to have run a cluster; you do need to have lived inside one.

• Active user of AI coding agents (Claude Code, Cursor, Copilot, agentic

CLIs, etc.). You should be able to walk us through specific tasks where they made you

faster, and specific tasks where they failed you and how you noticed. "I have tried it" is

not enough.

Bonus (real plus, not required)

• Infrastructure as Code: Terraform, Pulumi, or Ansible.

• Observability: Prometheus/Grafana, Datadog, OpenTelemetry, any APM.

• Have built or extended an LLM-based agent — a custom MCP server, a

scripted multi-step workflow, an internal tool that calls models in a loop. Anything beyond

chat-with-Claude.

• Exposure to GPU workloads, model serving (vLLM, Triton, TGI, etc.), or

ML pipelines.

What we don't care about

• Whether your degree is in CS — or whether you have a degree at all.

• Brand-name companies on your resume.

• Certifications. They are fine. They do not substitute for having shipped.

How we work

• We default to automation. If you do something manually twice, the third

time you script it or hand it to an agent.

• AI agents are part of the workflow, not a novelty. Expect interview

questions about exactly how you use them — and where you have caught them being

wrong.

• Small, reversible changes beat big-bang rollouts.

• Postmortems are blameless and written down.

• We push back on each other. If you only execute, you will be unhappy

here.

How to apply

Send:

• Your resume.

• A short note (≤200 words) describing one infra or automation problem you

solved, and how AI agents factored in — or did not, and why. We read these. Generic

notes get rejected.

Internal note — delete before posting externally

• Comp band, location policy, team name, and reporting line marked

[CONFIRM] need to be filled in before this goes external.

• The Required list is intentionally tight: CI/CD and Kubernetes basics

promoted from bonus. Expect this to filter ~80% of typical junior DevOps applicants. The

remaining pool will skew toward people who have actually shipped infra at a startup, not

bootcamp grads or pure cloud-cert holders.

• IaC, observability, agent-building, and GPU/ML serving stay as bonus.

Promoting any of these to required at 0–3 yrs collapses the pool to near-zero or forces

hiring senior people at junior comp. If you want IaC required, re-level this to mid (3–5

yrs) and raise the band.

• Screening implication: the resume screen should explicitly check for

CI/CD pipeline authorship and any K8s-touching production work. If neither is on the

resume, reject at screen. Do not waste interview slots.

• Pipeline watch: if fewer than ~15 qualified resumes after 2 weeks of

active sourcing, the first thing to relax is the AI-agent-fluency bar (move to bonus and

screen for it in interview instead). Do not relax the "shipped to production" requirement

— that is the load-bearing filter.

We are looking for a Senior Platform Engineer responsible for handling our GCP/AWS clouds. The candidate will be responsible for automating the deployment of cloud infrastructure and services to support application development and hosting (architecting, engineering, deploying, and operationally managing the underlying logical and physical cloud computing infrastructure).

Job Description:

● Collaborate with teams to build and deliver solutions implementing serverless, microservice-based, IaaS, PaaS, and containerized architectures in GCP/AWS environments.

●Responsible for deploying highly complex, distributed transaction processing systems.

● Work on continuous improvement of the products through innovation and learning. Someone with a knack for benchmarking and optimization

● Hiring, developing, and cultivating a high and reliable cloud support team ● Building and operating complex CI/CD pipelines at scale

● Work with GCP Services, Private Service Connect, Cloud Run, Cloud Functions, Pub/Sub, Cloud Storage, Networking

● Collaborate with Product Management and Product Engineering teams to drive excellence in Google Cloud products and features.

● Ensures efficient data storage and processing functions by company security policies and best practices in cloud security.

● Ensuring scaled database setup/monitoring with near zero downtime

A strong background in Azure OR Amazon Web Services (AWS) or a similar cloud platform is a must-have, certification is a plus.

Excellent technical skills and knowledge include but not limited to: cloud methodologies like PaaS and SaaS; programming languages such as Python, Java, .Net; orchestration systems such as Chef, Ansible, Terraform; Azure IaaS servers; PowerShell scripting.

Fully aware of the DevOps cycle with hands-on on deployment models to the cloud.

Experience working with Docker and related containerization technologies.

Experience working on orchestration platforms such as AKS, RedHat OpenShift etc.

Extensive knowledge working with logging and monitoring tools such as EFK, visualization tools such as Grafana and Prometheus.

Exposure to security alert monitoring tools.

DevOps Consultant!! MERN Stack Project Manager – Systems (Enterprise or Solutions) Architect needed!

Hello superstar,

I appreciate you taking time to read this. I have posted a job for developers to work on a start-up, the link is ......

I would need someone with DevOps experience, to ensure that the project is undertaken with the highest standards possible. I have had many experiences where ‘completed’ software after years of development was filled with bugs and it would be more cost-effective to start from scratch than to attempt to find and correct all the bugs.

I have attempted to learn as much as possible, but I now have an opportunity and it would better serve the venture to have someone handle the management of the project to ensure that;

• We choose the most appropriate technology
• We choose competent developers in those technologies
• The architecture and data modeling are clearly defined in a ‘blueprint’ plan
• A DevOps environment and processes are set up and the developers understand what is required
• Proper tests are carried out to ensure everything works as intended
• There are processes for testers to follow and competent testers are selected to follow them
• Accessibility, localization, and internationalization are planned ahead of time
• Security, scalability, and other future probabilities that I may not even be aware of are considered and planned ahead of time
• Documentation and code reviews, refactoring and other quality assurance processes are undertaken
• Working software is produced and systems that enable new developers or teams of people to easily take over and/or contribute new modules or updates in a controlled and organized fashion
• Cost estimates or budgets/projections or use of SaaS, hosting and other 3rd party services and applications

I am more concerned with a professional and world-class organizational system than with any particular type of software been produced as the strong foundation will enable anything to be creating with efficacy and precision.

Again, thank you for reading this, please reply with the word “superstar” anywhere in the second line of your response.  I look forward to hearing from you.

Warm wishes DevOps Evangelist,