DevOps Engineer

About the Role

We are looking for passionate and driven interns across multiple technology domains including Frontend Development, Backend Development, DevOps, AI/ML, and Data Engineering. This internship offers hands-on experience in real-world projects, collaboration with cross-functional teams, and exposure to modern tools and technologies. 

Domains & Responsibilities 

Frontend Development 

• Build responsive and user-friendly web interfaces  
• Translate UI/UX designs into functional applications  
• Optimize performance and ensure cross-browser compatibility  

 Backend Development 

• Develop APIs and server-side logic  
• Work with databases and data storage solutions  
• Ensure application security and performance  

 DevOps 

• Assist in CI/CD pipeline setup and automation  
• Manage deployments and cloud infrastructure  
• Monitor system performance and reliability  

 AI / Machine Learning 

• Develop and train ML models  
• Work on NLP, automation, or AI-driven features  
• Analyze datasets and evaluate model performance  

 Data Engineering 

• Build and maintain data pipelines (ETL/ELT)  
• Ensure data quality and availability  
• Work with large datasets and optimize data workflows  

 Required Skills (Any Domain) 

• Frontend: HTML, CSS, JavaScript, React/Vue/Angular  
• Backend: Node.js / Python / Java / PHP, APIs, databases  
• DevOps: Linux, Git, CI/CD basics, cloud fundamentals  
• AI/ML: Python, ML basics, TensorFlow/PyTorch/Scikit-learn  
• Data Engineering: SQL, Python, data processing concepts  

 Good to Have 

• Knowledge of Git and version control  
• Basic understanding of cloud platforms (AWS/Azure/GCP)  
• Problem-solving mindset and willingness to learn  
• Exposure to real-world or academic projects  

 Who Should Apply 

• Students or recent graduates in Computer Science, IT, or related fields  
• Candidates with strong interest in any of the above domains  
• Self-learners with project experience are highly encouraged  

 Internship Details 

• Duration: 3–6 months  
• Mode: Remote  
• Certificate + PPO (Pre-Placement Offer) based on performance  

 What You’ll Gain 

• Hands-on experience with real projects  
• Mentorship from experienced professionals  
• Exposure to industry tools and workflows  
• Opportunity to convert to a full-time role 

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

Salesforce DevOps/Release Engineer

Resource type - Salesforce DevOps/Release Engineer

Experience - 5 to 8 years

Norms - PF & UAN mandatory

Resource Availability - Immediate or Joining time in less than 15 days

Job - Remote

Shift timings - UK timing (1pm to 10 pm or 2pm to 11pm)

Required Experience:

• 5–6 years of hands-on experience in Salesforce DevOps, release engineering, or deployment management.
• Strong expertise in Salesforce deployment processes, including CI/CD pipelines.
• Significant hands-on experience with at least two of the following tools: Gearset, Copado,Flosum.
• Solid understanding of Salesforce architecture, metadata, and development lifecycle.
• Familiarity with version control systems (e.g., Git) and agile methodologies

Key Responsibilities:

• Design, implement, and manage CI/CD pipelines for Salesforce deployments using Gearset, Copado, or Flosum.
• Automate and optimize deployment processes to ensure efficient, reliable, and repeatable releases across Salesforce environments.
• Collaborate with development, QA, and operations teams to gather requirements and ensurealignment of deployment strategies.
• Monitor, troubleshoot, and resolve deployment and release issues.
• Maintain documentation for deployment processes and provide training on best practices.
• Stay updated on the latest Salesforce DevOps tools, features, and best practices.

Technical Skills:

• Deployment ToolsHands-on with Gearset, Copado, Flosum for Salesforce deployments
• CI/CDBuilding and maintaining pipelines, automation, and release management
• Version ControlProficiency with Git and related workflows
• Salesforce PlatformUnderstanding of metadata, SFDX, and environment management
• Scripting
• Familiarity with scripting (e.g., Shell, Python) for automation (preferred)
• Communication
• Strong written and verbal communication skills

Preferred Qualifications:

Bachelor’s degree in Computer Science, Information Technology, or related field.

Certifications:

Salesforce certifications (e.g., Salesforce Administrator, Platform Developer I/II) are a plus.

Experience with additional DevOps tools (Jenkins, GitLab, Azure DevOps) is beneficial.

Experience with Salesforce DX and deployment strategies for large-scale orgs. 

Azure DeVops

On premises to Azure Migration

Docker, Kubernetes

Terraform CI CD pipeline

9+ Location

Budget – BG, Hyderabad, Remote , Hybrid –

Budget – up to 30 LPA

Position: DevOps Engineer

Job Description

The candidate should have the following Skills:

- Hands-on experience with DevOps & CICD open source tools (Jenkins, ), including AWS DevOps services (CodePipeline, CloudFormation, etc).

- Experience in building and deploying using Java/Python/Node.js on Cloud infrastructure (Docker or Kubernetes containers or Lambda.)

- Exposure to Cloud operations, releases, and configuration management

- Experience in implementing Non-functional requirements for microservices, including performance, security, compliance, HA and Disaster Recovery.

- Good soft skills, great attitude, and passion for working in a product startup environment

Total Experience of 2-5 years post BE or BTech or MCA in Computer Science Engineering.

• Have 3+ years of experience in Python development
• Be familiar with common database access patterns
• Have experience with designing systems and monitoring metrics, looking at graphs.
• Have knowledge of AWS, Kubernetes and Docker.
• Be able to work well in a remote development environment.
• Be able to communicate in English at a native speaking and writing level.
• Be responsible to your fellow remote team members.
• Be highly communicative and go out of your way to contribute to the team and help others

We are looking for an experienced DevOps engineer that will help our team establish DevOps practice. You will work closely with the technical lead ( and/or CTO ) to identify and establish DevOps practices in the company.

You will help us build scalable, efficient cloud infrastructure. You’ll implement monitoring for automated system health checks. Lastly, you’ll build our CI pipeline, and train and guide the team in DevOps practices.

Responsibilities

• Implement and own the CI.
• Manage CD tooling.
• Implement and maintain monitoring and alerting.
• Build and maintain highly available production systems.

Qualification- B.tech in IT