DevOps and Cloud Engineer

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).

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

Roles and Responsibilities:

• AWS Cloud Management: Design, deploy, and manage AWS cloud infrastructure. Optimize and maintain cloud resources for performance and cost efficiency. Monitor and ensure the security of cloud-based systems.
• Automated Provisioning: Develop and implement automated provisioning processes for infrastructure deployment. Utilize tools like Terraform and Packer to automate and streamline the provisioning of resources.
• Infrastructure as Code (IaC): Champion the use of Infrastructure as Code principles. Collaborate with development and operations teams to define and maintain IaC scripts for infrastructure deployment and configuration.
• Collaboration and Communication: Work closely with cross-functional teams to understand project requirements and provide DevOps expertise. Communicate effectively with team members and stakeholders regarding infrastructure changes, updates, and improvements.
• Continuous Integration/Continuous Deployment (CI/CD): Implement and maintain CI/CD pipelines to automate software delivery processes. Ensure reliable and efficient deployment of applications through the development lifecycle.
• Performance Monitoring and Optimization: Implement monitoring solutions to track system performance, troubleshoot issues, and optimize resource utilization. Proactively identify opportunities for system and process improvements. 

Mandatory Skills:

• Proven experience as a DevOps Engineer or similar role, with a focus on AWS.
• Strong proficiency in automated provisioning and cloud management.
• Experience with Infrastructure as Code tools, particularly Terraform and Packer.
• Solid understanding of CI/CD pipelines and version control systems.
• Strong scripting skills (e.g., Python, Bash) for automation tasks.
• Excellent problem-solving and troubleshooting skills.
• Good interpersonal and communication skills for effective collaboration.

Secondary Skills:

• AWS certifications (e.g., AWS Certified DevOps Engineer, AWS Certified Solutions Architect).
• Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).
• Knowledge of microservices architecture and serverless computing.
• Familiarity with monitoring and logging tools (e.g., CloudWatch, ELK stack).

You will be responsible for:

• Managing all DevOps and infrastructure for Sizzle
• We have both cloud and on-premise servers
• Work closely with all AI and backend engineers on processing requirements and managing both development and production requirements
• Optimize the pipeline to ensure ultra fast processing
• Work closely with management team on infrastructure upgrades

You should have the following qualities:

• 3+ years of experience in DevOps, and CI/CD
• Deep experience in: Gitlab, Gitops, Ansible, Docker, Grafana, Prometheus
• Strong background in Linux system administration
• Deep expertise with AI/ML pipeline processing, especially with GPU processing. This doesn’t need to include model training, data gathering, etc. We’re looking more for experience on model deployment, and inferencing tasks at scale
• Deep expertise in Python including multiprocessing / multithreaded applications
• Performance profiling including memory, CPU, GPU profiling
• Error handling and building robust scripts that will be expected to run for weeks to months at a time
• Deploying to production servers and monitoring and maintaining the scripts
• DB integration including pymongo and sqlalchemy (we have MongoDB and PostgreSQL databases on our backend)
• Expertise in Docker-based virtualization including - creating & maintaining custom Docker images, deployment of Docker images on cloud and on-premise services, monitoring of production Docker images with robust error handling
• Expertise in AWS infrastructure, networking, availability

Optional but beneficial to have:

• Experience with running Nvidia GPU / CUDA-based tasks
• Experience with image processing in python (e.g. openCV, Pillow, etc)
• Experience with PostgreSQL and MongoDB (Or SQL familiarity)
• Excited about working in a fast-changing startup environment
• Willingness to learn rapidly on the job, try different things, and deliver results
• Bachelors or Masters degree in computer science or related field
• Ideally a gamer or someone interested in watching gaming content online

Skills:

DevOps, Ansible, CI/CD, GitLab, GitOps, Docker, Python, AWS, GCP, Grafana, Prometheus, python, sqlalchemy, Linux / Ubuntu system administration

Seniority: We are looking for a mid to senior level engineer

Salary: Will be commensurate with experience. 

Who Should Apply:

If you have the right experience, regardless of your seniority, please apply.

Work Experience: 3 years to 6 years

Role – Devops

Experience 3 – 6 Years

Roles & Responsibilities –

• 3-6 years of experience in deploying and managing highly scalable fault resilient systems
• Strong experience in container orchestration and server automation tools such as Kubernetes, Google Container Engine, Docker Swarm, Ansible, Terraform  

• Strong experience with Linux-based infrastructures, Linux/Unix administration, AWS, Google Cloud, Azure

• Strong experience with databases such as  MySQL, Hadoop, Elasticsearch, Redis, Cassandra, and MongoDB.

• Knowledge of scripting languages such as Java, JavaScript, Python, PHP, Groovy, Bash.

• Experience in configuring CI/CD pipelines using Jenkins, GitLab CI, Travis.
• Proficient in technologies such as Docker, Kafka, Raft and Vagrant

• Experience in implementing queueing services such as RabbitMQ, Beanstalkd, Amazon SQS and knowledge in ElasticStack is a plus.

Job Description:

• Hands on experience with Ansible & Terraform.
• Scripting language, such as Python or Bash or PowerShell is required and willingness to learn and master others. 
• Troubleshooting and resolving automation, build, and CI/CD related issues (in cloud environment like AWS or Azure).
• Experience with Kubernetes is mandate.
• To develop and maintain tooling and environments for test and production environments.
• Assist team members in the development and maintenance of tooling for integration testing, performance testing, security testing, as well as source control systems (that includes working in CI systems like Azure DevOps, Team City, and orchestration tools like Octopus).
• Good with Linux environment.

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.