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Azure DevOps + Python
Azure DevOps + Python

Azure DevOps + Python at Wissen Technology · Bengaluru (Bangalore) · 5 - 14 years · Profitable · Posted 30 Sep 2026

Wissen Technology's logo

Azure DevOps + Python

Shakthi M's profile picture
Posted by Shakthi M
5 - 14 yrs
Best in industry
Bengaluru (Bangalore)
Skills
skill iconPython
Azure
Terraform
DevOps
  • 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

 

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About Wissen Technology

Founded :
2015
Type :
Products & Services
Size :
1000-5000
Stage :
Profitable

About

The Wissen Group was founded in the year 2000. Wissen Technology, a part of Wissen Group, was established in the year 2015. Wissen Technology is a specialized technology company that delivers high-end consulting for organizations in the Banking & Finance, Telecom, and Healthcare domains.

With offices in US, India, UK, Australia, Mexico, and Canada, we offer an array of services including Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud, Mobility, Agile & DevOps, Quality Assurance & Test Automation.


Leveraging our multi-site operations in the USA and India and availability of world-class infrastructure, we offer a combination of on-site, off-site and offshore service models. Our technical competencies, proactive management approach, proven methodologies, committed support and the ability to quickly react to urgent needs make us a valued partner for any kind of Digital Enablement Services, Managed Services, or Business Services.


We believe that the technology and thought leadership that we command in the industry is the direct result of the kind of people we have been able to attract, to form this organization (you are one of them!).


Our workforce consists of 1000+ highly skilled professionals, with leadership and senior management executives who have graduated from Ivy League Universities like MIT, Wharton, IITs, IIMs, and BITS and with rich work experience in some of the biggest companies in the world.


Wissen Technology has been certified as a Great Place to Work®. The technology and thought leadership that the company commands in the industry is the direct result of the kind of people Wissen has been able to attract. Wissen is committed to providing them the best possible opportunities and careers, which extends to providing the best possible experience and value to our clients.

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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.


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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. 


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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.
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  • 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

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FinOps, Cost Governance & Security

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  • 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

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  • 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. 


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  • 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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City Locations: Bengaluru

*Key Responsibilities*

Devops Developer (Azure)

Azure L2 Support | Specialist | Infrastructure Operations-260006F2- Certificate & DNS Management- Monitoring & Observability- Azure Operations & Compliance- Migration: Open Cloud TnC- Reliability & Operations Excellence (OPS)

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Desire candidate

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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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