Azure Devops Engineer

Required

• Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent experience).
• 3+ years of hands-on experience with Microsoft Azure, including IaaS, PaaS, networking, identity (Entra ID), and governance services.
• 2+ years of experience with DevOps tooling and practices, including CI/CD pipelines (Azure DevOps or GitHub Actions), Infrastructure as Code (Terraform, Bicep, or ARM), and version control (Git).
• 2+ years' experience in infrastructure design, platform engineering, or architecture.
• Strong proficiency with automation and scripting — PowerShell, Azure CLI, Python, or Bash.
• Solid understanding of containerisation (Docker) and familiarity with orchestration platforms (Azure Kubernetes Service).
• Deep understanding of cloud architecture, deployment patterns, and management best practices, including the Azure Well-Architected Framework.
• Experience defining standards, governance frameworks, and reference architectures for cloud platform consumption.
• Strong knowledge of networking concepts, storage configurations, virtualisation technologies, and disaster recovery/backup design for hybrid environments.
• Experience with Azure DevOps (Repos, Pipelines, Boards, Artifacts) or equivalent platforms.
• Familiarity with identity and access management (IAM), including Entra ID, RBAC, PIM.
• Strong understanding of security, compliance requirements, and IT governance frameworks (ITIL, COBIT, or similar).

Preferred

• Experience with multi-cloud environments or hybrid cloud integration.
• Familiarity with GitOps, policy-as-code (e.g. Azure Policy, OPA), and secrets management (Azure Key Vault).
• Experience implementing DevSecOps practices — automated scanning, compliance-as-code, and shift-left security.
• Experience designing monitoring and observability frameworks (rather than just consuming them).
• Certifications — any of the following are highly valued:
• Microsoft Certified: Azure Administrator Associate (AZ-104)
• Microsoft Certified: Azure Solutions Architect Expert (AZ-305)
• Microsoft Certified: DevOps Engineer Expert (AZ-400)
• HashiCorp Certified: Terraform Associate
• ITIL Foundation or Practitioner
• CISSP or similar security certification

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).

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)

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

ROLE & RESPONSIBILITIES:

We are hiring a Senior DevSecOps / Security Engineer with 8+ years of experience securing AWS cloud, on-prem infrastructure, DevOps platforms, MLOps environments, CI/CD pipelines, container orchestration, and data/ML platforms. This role is responsible for creating and maintaining a unified security posture across all systems used by DevOps and MLOps teams — including AWS, Kubernetes, EMR, MWAA, Spark, Docker, GitOps, observability tools, and network infrastructure.

KEY RESPONSIBILITIES:

1.     Cloud Security (AWS)-

• Secure all AWS resources consumed by DevOps/MLOps/Data Science: EC2, EKS, ECS, EMR, MWAA, S3, RDS, Redshift, Lambda, CloudFront, Glue, Athena, Kinesis, Transit Gateway, VPC Peering.
• Implement IAM least privilege, SCPs, KMS, Secrets Manager, SSO & identity governance.
• Configure AWS-native security: WAF, Shield, GuardDuty, Inspector, Macie, CloudTrail, Config, Security Hub.
• Harden VPC architecture, subnets, routing, SG/NACLs, multi-account environments.
• Ensure encryption of data at rest/in transit across all cloud services.

2.     DevOps Security (IaC, CI/CD, Kubernetes, Linux)-

Infrastructure as Code & Automation Security:

• Secure Terraform, CloudFormation, Ansible with policy-as-code (OPA, Checkov, tfsec).
• Enforce misconfiguration scanning and automated remediation.

CI/CD Security:

• Secure Jenkins, GitHub, GitLab pipelines with SAST, DAST, SCA, secrets scanning, image scanning.
• Implement secure build, artifact signing, and deployment workflows.

Containers & Kubernetes:

• Harden Docker images, private registries, runtime policies.
• Enforce EKS security: RBAC, IRSA, PSP/PSS, network policies, runtime monitoring.
• Apply CIS Benchmarks for Kubernetes and Linux.

Monitoring & Reliability:

• Secure observability stack: Grafana, CloudWatch, logging, alerting, anomaly detection.
• Ensure audit logging across cloud/platform layers.

3.     MLOps Security (Airflow, EMR, Spark, Data Platforms, ML Pipelines)-

Pipeline & Workflow Security:

• Secure Airflow/MWAA connections, secrets, DAGs, execution environments.
• Harden EMR, Spark jobs, Glue jobs, IAM roles, S3 buckets, encryption, and access policies.

ML Platform Security:

• Secure Jupyter/JupyterHub environments, containerized ML workspaces, and experiment tracking systems.
• Control model access, artifact protection, model registry security, and ML metadata integrity.

Data Security:

• Secure ETL/ML data flows across S3, Redshift, RDS, Glue, Kinesis.
• Enforce data versioning security, lineage tracking, PII protection, and access governance.

ML Observability:

• Implement drift detection (data drift/model drift), feature monitoring, audit logging.
• Integrate ML monitoring with Grafana/Prometheus/CloudWatch.

4.     Network & Endpoint Security-

• Manage firewall policies, VPN, IDS/IPS, endpoint protection, secure LAN/WAN, Zero Trust principles.
• Conduct vulnerability assessments, penetration test coordination, and network segmentation.
• Secure remote workforce connectivity and internal office networks.

5.     Threat Detection, Incident Response & Compliance-

• Centralize log management (CloudWatch, OpenSearch/ELK, SIEM).
• Build security alerts, automated threat detection, and incident workflows.
• Lead incident containment, forensics, RCA, and remediation.
• Ensure compliance with ISO 27001, SOC 2, GDPR, HIPAA (as applicable).
• Maintain security policies, procedures, RRPs (Runbooks), and audits.

IDEAL CANDIDATE:

• 8+ years in DevSecOps, Cloud Security, Platform Security, or equivalent.
• Proven ability securing AWS cloud ecosystems (IAM, EKS, EMR, MWAA, VPC, WAF, GuardDuty, KMS, Inspector, Macie).
• Strong hands-on experience with Docker, Kubernetes (EKS), CI/CD tools, and Infrastructure-as-Code.
• Experience securing ML platforms, data pipelines, and MLOps systems (Airflow/MWAA, Spark/EMR).
• Strong Linux security (CIS hardening, auditing, intrusion detection).
• Proficiency in Python, Bash, and automation/scripting.
• Excellent knowledge of SIEM, observability, threat detection, monitoring systems.
• Understanding of microservices, API security, serverless security.
• Strong understanding of vulnerability management, penetration testing practices, and remediation plans.

EDUCATION:

• Master’s degree in Cybersecurity, Computer Science, Information Technology, or related field.
• Relevant certifications (AWS Security Specialty, CISSP, CEH, CKA/CKS) are a plus.

PERKS, BENEFITS AND WORK CULTURE:

• Competitive Salary Package
• Generous Leave Policy
• Flexible Working Hours
• Performance-Based Bonuses
• Health Care Benefits

DevOps & Automation:

• Experience in CI/CD tools like Azure DevOps, YAML, Git, and GitHub. Capable of automating build, test, and deployment processes to streamline application delivery.
• Hands-on experience with Infrastructure as Code (IaC) tools such as Bicep (preferred), Terraform, Ansible, and ARM Templates.

Cloud Services & Architecture:

• Experience in Azure Cloud services, including Web Apps, AKS, Application Gateway, APIM, and Logic Apps.
• Good understanding of cloud design patterns, security best practices, and cost optimization strategies.

Scripting & Automation:

• Experience in developing and maintaining automation scripts using PowerShell to manage, monitor, and support applications.
• Familiar with Azure CLI, REST APIs, and automating workflows using Azure DevOps Pipelines.

Data Integration & ADF:

• Working knowledge or basic hands-on experience with Azure Data Factory (ADF), focusing on developing and managing data pipelines and workflows.
• Knowledge of data integration practices, including ETL/ELT processes and data transformations.

Application Management & Monitoring:

• Ability to provide comprehensive support for both new and legacy applications.
• Proficient in managing and monitoring application performance using tools like Azure Monitor, Log Analytics, and Application Insights.
• Understanding of application security principles and best practices.

Database Skills:

• Basic experience of SQL and Azure SQL, including database backups, restores, and application data management.

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.

• Proficiency in Integration of various Azure resources (IaaS and PaaS - SQL DB , App Service , Application Insights , databricks , Storage accounts etc) to deliver an end to end automation.
• Thorough understanding of Continuous integration and continuous delivery using Azure DevOps/VSTS.
• Performing cost analysis of the Azure platform to identify where cost efficiencies could be had.
• Proficiency and thorough understanding of Azure RBAC model.
• Sound understanding of Azure Active directory and conditional access policies.
• Good grasp of Azure governance principles and hands-on experience in rolling out compliance and governance polices.
• Proficiency in developing infrastructure automation scripts in the form of ARM templates and Azure Power Shell scripts which can then be provided to application teams as consumables.
• Effective communication skills, both written and verbal for technical and non-technical audiences.
• Good working and hands on knowledge of Azure IaaS , Vnet , Subnets , Firewalls and NSG. Sound understanding of networking knowledge on DNA and Firewall security like Palo Alto.
• Experience working with Confluence, JIRA, Bitbucket, git, Jenkins, Sonar for collaboration and continuous integration.
• Experience with agile methods, along with having found their limitations and ways to overcome them.

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,