Azure DevOps AI Architect

• Strong hands-on experience in Microsoft Azure Cloud.
• Good understanding of Azure services such as Compute, Storage, Event Hub, Event Subscription, Storage Queue, and PaaS services.
• Basic understanding of Azure AI Foundry and AI-related Azure service setup.
• Good Azure networking basics: VNet, subnet, routing, and basic troubleshooting.
• Strong knowledge of Terraform, especially:
• Terraform state
• plan / apply
• troubleshooting failures
• migration risks
• Terraform Enterprise concepts
• Strong Python coding capability, not just basic scripting.
• Experience using Python for API integration, automation, JSON/YAML handling, and internal tooling.
• Good understanding of CI/CD pipelines.
• Ability to troubleshoot pipeline failures.
• Comfortable with YAML and JSON.
• Ability to troubleshoot Azure infrastructure/platform issues.
• Ability to collect logs/evidence and coordinate with network/app/Microsoft support teams.
• Basic awareness of agentic AI / LLM concepts.
• Awareness of security and cost best practices.

Good to Have Skills

• Hands-on experience with Harness.
• Hands-on experience with Terraform Enterprise.
• Exposure to LangGraph / LangChain.
• Exposure to agentic AI workflows or skill creation.
• Exposure to Claude or enterprise LLM integrations.
• Knowledge of Azure ML Workspace, model registry, and managed endpoints.
• MLOps / LLMOps knowledge.
• FinOps / Azure cost optimization experience.
• Azure certifications: AZ-104, AZ-305, AZ-400, AZ-500.

Screening Priority:

Azure Cloud + Terraform + Python Coding + CI/CD Troubleshooting + YAML/JSON + Basic Agentic AI Awareness

We are looking for a hands-on Azure DevOps & Infrastructure Engineer to manage enterprise Azure environments, automate infrastructure, build CI/CD pipelines, and support cloud modernization initiatives.

🔑 Key Responsibilities

• Design, implement & support CI/CD pipelines and deployment automation

• Perform TFS / Azure DevOps Server → Azure DevOps Services migration

• Build & manage Azure infrastructure using Infrastructure as Code (IaC)

• Support Azure cloud infrastructure, networking, security, monitoring & production environments

• Drive cloud migration, application modernization & platform transformation initiatives

• Work with Terraform, containerization, DevSecOps & cloud automation

• Troubleshoot infrastructure/deployment issues and support incident & on-call operations

• Create technical documentation, runbooks and deployment standards

🎯 Mandatory Requirements

✅ AZ-204 – Azure Developer Associate – Mandatory

✅ 5–8 years total IT experience

✅ 3+ years hands-on Azure DevOps / Azure Infrastructure experience

✅ Strong experience in CI/CD & Azure DevOps

✅ Hands-on experience with TFS / Azure DevOps Server to Azure DevOps Services migration

✅ Strong understanding of Azure cloud infrastructure & cloud operations

✅ Experience with IaC, provisioning & infrastructure automation

✅ Exposure to cloud/data migration and application modernization

✅ Experience supporting Azure networking, security & monitoring

✅ Experience in production support / managed services / cloud operations

✅ Willingness to work UK/US shifts and participate in on-call support

⭐ Preferred / Optional

• AZ-400 – Microsoft Certified DevOps Engineer Expert

• AZ-104 – Azure Administrator Associate

• HashiCorp Terraform Associate

• Container platforms, orchestration & DevSecOps experience

🎓 Education: Bachelor's degree in Computer Science / IT / Engineering or related field.

Azure DevOps Engineer

Experience

5-10 years of hands-on experience in Platform Engineering, Cloud Engineering, SRE, DevOps or Infrastructure Engineering roles.

Priority 1 – Must Have (Hands-On)

Azure Cloud Platform

·        Strong hands-on experience supporting Azure workloads in production environments.

·        Experience designing, building and supporting Azure infrastructure using Terraform.

·        Good understanding of Azure networking and connectivity patterns.

·        Experience supporting:

Ø AKS

Ø Application Gateway

Ø Azure Traffic Manager

Ø Key Vault

Ø Azure Monitor / Log Analytics

Ø Managed Identities

Ø Service Principals

Ø Private Endpoints

Ø VNets, NSGs and Route Tables

Kubernetes / AKS

• Strong practical experience operating and supporting AKS.
• Ability to troubleshoot:

Ø Pod failures

Ø Ingress issues

Ø DNS issues

Ø SSL/TLS certificate issues

Ø Network routing issues

Ø Performance and availability incidents

• Experience with:

Ø Helm

Ø Ingress Controllers

Ø Cluster upgrades

Ø Scaling

Ø Monitoring

Terraform

·        Strong hands-on experience writing and maintaining Terraform.

·        Experience creating reusable modules.

·        Experience managing:

·        State files

·        Remote backends

·        Environment promotion

·        Infrastructure lifecycle

Linux & Scripting

·        Strong Linux administration fundamentals.

·        Practical experience troubleshooting production issues.

·        Bash scripting mandatory.

·        Python desirable.

Application Support / Troubleshooting

Must be comfortable supporting business applications end-to-end.

 Priority 2 – Highly Desirable

GitHub & DevOps Platform

Hands-on experience with:

·        GitHub Enterprise

·        GitHub Actions

·        Shared workflows

·        Reusable pipelines

·        Repository onboarding

·        Branch protections

·        GitHub security features

Experience supporting:

·        Runner issues

·        Disk space issues

·        Network connectivity issues

·        Dependency failures

·        Self-hosted runners lifecycle management

API Management

Pipeline failures

GitOps

Experience with:

·        ArgoCD

·        GitOps deployment models

·        Kubernetes deployment automation

Monitoring & Observability

Experience working with:

·        Prometheus

·        Grafana

·        Azure Monitor

·        Log Analytics

·        Application Insights

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

Job Description:

Job title : Cloud Architect

Experience: 10+ years

Location: Chennai / Pune / Hyderabad / Bangalore

Shift: UK Shift

Work Mode: Onsite(WFO)

Notice Period: Immediate Joiner/ serving notice period only

Project Scope:

This engagement automates end-to-end infrastructure build provisioning across on-prem and Azure. The team will build a shared ServiceNow-led intake, approval, orchestration, and closed-loop status model, using Jenkins/Ansible for on-prem builds and Azure DevOps/Terraform for cloud builds. Automation includes standards, security/compliance controls, scan gates, CMDB/change updates, and handover.    

Roles and Responsibilities:

Define Azure automation architecture, governance, and reusable cloud build patterns.            

Own Azure architecture for automated build provisioning using the ServiceNow-led control plane.

Define approved build patterns, SKUs, landing-zone integration, Terraform standards, Azure DevOps architecture, and guardrails.

Translate security, compliance, resiliency, tagging, cost, and data-residency requirements into automated controls.

Design ServiceNow, rules engine, Azure DevOps, Terraform, Azure Policy, CMDB, and callback integrations.

Review solution designs and assure quality with cloud, security, finance, and platform teams.

Required Skills:

Azure landing zones, networking, RBAC, Key Vault, Azure Policy, Terraform, Azure DevOps, FinOps, ServiceNow APIs.          

10+ years in infrastructure/cloud engineering; 5+ years designing Azure solutions.

Bachelor’s degree or equivalent experience; Azure Solutions Architect certification preferred.

Primary (Must Have):

 5-7 years of total experience in IT industry

 Necessary to have exposure to Azure Cloud

 5-7 years of experience Build/Release and DevOps combined for Saas/Web/Desktop applications

 5-7 years working with CI / CD like Jenkins or Bamboo or other tools

 Experience in Kubernetes, Swarm and Docker

 Experience in working with Linux (Centos/Ubuntu)

 Experience with configuration and management tools (i.e. Terraform, Ansible, Salt)

 Experience in architecting, maintaining, and streamlining our automated build and release pipeline from code compilation, automated testing, to deploying releases to multiple environments

 You should be able to drive adoption of CI/CD, deployment automation, and release engineering standard methodologies

 Detail-oriented and great problem solver

 Comfortable giving feedback to team members and handling personal situations

 Excellent at multi-tasking and able to handle competing priorities

 Problem solving, digging into issues and owning tasks to completion

 Strong team player who is open to give and receive feedback

 A passion for technology and thrives in a dynamic environment with a focus on creative innovation over absolute completion

 Communication and presentation skills

Key Responsibilities:            

 Responsible for the continuous and on-time delivery of application releases supporting mission-critical services

 Support and improve our tools for continuous integration (CI) and continuous delivery (CD). You can demonstrate measurable improvements in our delivery pipelines

 Responsible for navigating cloud solutions, on-premise solutions, and hybrid solutions

 Responsible for infrastructure as code (IaC) tooling

 Build automated release pipelines that package, test and deploy code

 Build out and maintain a suitable tracking dashboards and metrics

Hiring for AI Engineer

Exp: 6 - 8 yrs

Edu : BE/B.Tech/MCA

Work Location : Pune

Skill Set:

- Total experience ranging from 6–8 years in software engineering/AI roles

- Min 5 years strong programming experience in Python is a MUST

- Min 3.5 years hands-on experience in AI with LLMs, RAG pipelines, and AI frameworks

- Experience with cloud platforms (AWS/Azure/GCP)

🚀 Hiring: Senior Azure Platform Engineer | Azure | Terraform | Kubernetes

📍 Location: India

💼 Employment: Full-Time | Long-Term

🎯 Experience: 10+ Years | 8+ Years Hands-on Azure

🔑 What We’re Looking For

▪️ Strong expertise in Azure Cloud Platform & Landing Zone Architecture

▪️ Advanced hands-on experience with Terraform & reusable IaC modules

▪️ Expertise in Kubernetes, Helm & container platforms

▪️ Strong understanding of Azure Networking, Entra ID, RBAC & Azure Policy

▪️ Experience with GitHub, GitHub Actions / Azure Pipelines & CI/CD

▪️ Hands-on GitOps & ArgoCD experience

▪️ Strong observability skills with Prometheus, Grafana & Azure Monitor

▪️ Experience designing and supporting microservices architectures

▪️ Knowledge of security, policy-as-code and IaC security scanning

▪️ Exposure to Azure Arc / Azure Local / Azure Stack HCI is a plus

We’re on hunt for AI Architect

Responsibilities:

• 10–15+ years overall experience, with recent hands-on AI/GenAI architecture ownership.
• Must have architected enterprise AI platforms/solutions end-to-end, not just individual ML models or PoCs.
• Strong GenAI/LLM production experience: RAG, embeddings, vector DBs, hybrid search, reranking, evaluation, guardrails.
• Strong Agentic AI understanding: agents, tool calling, workflows, orchestration, human-in-the-loop.
• Experience taking AI solutions from architecture → production → scale, ideally across multiple business teams/use cases.
• Strong cloud architecture — Azure/AWS preferred; hybrid/on-prem experience is a plus.
• Must understand enterprise security, governance, Responsible AI, observability and LLMOps/MLOps.
• Should be able to articulate build-vs-buy, MVP-vs-target architecture, cost/performance/security tradeoffs.
• Strong stakeholder-facing / consulting ability — can work with business leaders, engineering, security and data teams and influence without authority.

There is scope to move to the US for this role if you are aligned for the same, else this will be a WFO role from Hyderabad location

EMBEDDED AI ENGINEERING POD

AI Implementation Engineer Role

Level: AI Implementation Engineer Senior / Advanced - 6+ years

Practice: Wissen GenAI

Locations: Mumbai / Bengaluru / New York - hybrid, embedded with delivery teams

Reports to: EMBEDDED AI PRACTICE Senior AI Engineering Specialist (Architect); Wissen GenAI Program Lead

Embedded inside enterprise delivery teams, you work closely with global, cross-regional teams to turn prioritized GenAI use cases into production software - building, integrating, and hardening Azure-based AI solutions and accelerating adoption within the teams you join.

You deliver production software and help the teams you join work faster.

As an embedded AI Implementation Engineer, you help convert prioritized use cases into shipped, governed, measurable software.

Key responsibilities

1. Build and ship.

Implement GenAI features end to end on Azure - RAG pipelines, agents, APIs, and UI integrations - against enterprise systems and data.

2. Embed and enable.

Work inside the delivery pods: pair with their engineers, remove blockers, and transfer GenAI skills so adoption sticks after you move on.

3. Productionize.

Add evaluation, observability, guardrails, caching, and CI/CD so prototypes become reliable, cost-efficient services.

4. Integrate securely.

Connect to enterprise data with correct access control, secrets management, and compliance with enterprise security standards and handling of sensitive data.

5. Iterate on quality.

Use evaluation results and user feedback to improve grounding, accuracy, latency, and cost.

6. Measure.

Track delivery and quality metrics that roll up to the program's targets.

Must-have qualifications

• 6+ years in software engineering, with 2+ years building GenAI/LLM applications in production.
• Strong Python (incl. async) and Java (the primary enterprise application stack; Spring a plus); solid API and systems design.
• Azure GenAI hands-on: Azure OpenAI, Azure AI Foundry, Azure AI Search for RAG, Azure AI Document Intelligence (IDP), and Prompt Flow.
• Agent frameworks: Microsoft Agent Framework / Semantic Kernel / AutoGen (or LangChain / LangGraph) and tool / function calling.

Preferred

• RAG fundamentals: embeddings, chunking, vector search, reranking, and grounding.
• Data platforms: Snowflake including Cortex AI (Cortex Search, LLM functions) and SQL, for accessing and grounding on enterprise data.
• Prompt engineering as versioned code; building and running evaluations.
• DevOps: Azure DevOps / GitHub Actions, Docker, AKS / Azure Functions, and observability.
• Financial services or other regulated environments.
• Front-end (React) for AI-assisted UX; streaming and token level operations.
• Azure AI Content Safety and responsible-AI practices.
• Certification: Azure AI Engineer Associate.

What success looks like - first 6 to 12 months

• Multiple GenAI features shipped to production within the embedded delivery pods.
• Measurable adoption and productivity uplift in the teams you support.
• Reusable components adopted from the architects' reference framework.
• Clear contribution to faster time-to-market and lower defect rates.