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🚀 Hiring: Senior DevOps Engineer | Gurugram | Immediate Joiner
📍 Location: Gurugram (On-Site)
💼 Employment Type: Full-Time
⏱️ Joining: Immediate Joiner Preferred
🎓 Qualification: B.Tech in Computer Science / Engineering
🧑💻 Experience: 5+ Years
About the Role
Aaizel Tech Labs is looking for a highly skilled Senior DevOps Engineer to join our rapidly growing AI-driven startup, building and deploying cutting-edge enterprise AI/ML solutions.
This is a critical role where you will shape our infrastructure, deployment pipelines, cloud architecture, and ML operations to support large-scale enterprise clients.
You’ll work at the intersection of DevOps, MLOps, Cloud, Data Engineering, and AI/ML, ensuring our ML-powered applications are deployed securely, reliably, and at scale.
🔧 Key Responsibilities
☁️ DevOps & Cloud
Design and manage cloud-native infrastructure across AWS, Azure, or GCP.
Build and maintain CI/CD pipelines using Jenkins, GitLab CI, GitHub Actions, or CircleCI.
Implement Infrastructure as Code using Terraform, CloudFormation, Pulumi, or Ansible.
Manage Docker containers and Kubernetes clusters for ML workloads.
Implement monitoring, logging, alerting, security, and compliance solutions using tools such as Prometheus, Grafana, ELK, Datadog, or New Relic.
🤖 MLOps & Model Deployment
Design and maintain end-to-end ML pipelines from development to production.
Build ML-focused CI/CD pipelines using MLflow, Kubeflow, or custom solutions.
Implement model versioning, experiment tracking, and model registries.
Monitor model performance and drift, and implement automated retraining.
Manage feature stores and data pipelines for batch and real-time inference.
Build scalable infrastructure for high-volume ML workloads.
📊 Data Engineering & Real-Time Processing
Build large-scale data pipelines using Apache Airflow, Prefect, Dagster, or similar tools.
Design real-time streaming architectures using Kafka, Spark, Flink, or Redis.
Manage structured and unstructured data platforms.
Implement data validation, quality checks, lineage, security, and compliance.
Optimize data processing for performance and cost efficiency.
🏢 Enterprise Platform Operations
Ensure 99.9%+ availability and reliability of enterprise platforms.
Implement auto-scaling for variable ML workloads.
Manage multi-tenant architectures and data isolation.
Optimize cloud resource utilization and infrastructure costs.
Implement disaster recovery and backup strategies.
Build 24x7 monitoring and alerting for mission-critical applications.
💻 Technical Skills
Programming & Scripting
Advanced Python — primary language for automation and ML operations
Bash/Shell scripting
YAML/JSON
SQL
Basic Go or Java is an advantage
Cloud & Infrastructure
AWS / Azure / GCP
Docker & Kubernetes
Terraform / CloudFormation / Pulumi / Ansible
Jenkins / GitLab CI / GitHub Actions / CircleCI
Prometheus / Grafana / ELK / Datadog / New Relic
Data Technologies
Apache Airflow / Prefect / Dagster / Apache NiFi
Apache Kafka / Spark / Flink / Redis
PostgreSQL / MongoDB / Elasticsearch / ClickHouse
Snowflake / BigQuery / Redshift / Databricks
DVC / LakeFS / Pachyderm
MLOps & AI/ML
TensorFlow / PyTorch / Scikit-learn / Keras / XGBoost
MLflow / Kubeflow / Metaflow / DVC / Weights & Biases
TensorFlow Serving / TorchServe / Seldon Core / KFServing
MLflow / Neptune.ai / Weights & Biases / Comet
🎯 Required Qualifications
5–8+ years of experience in DevOps/MLOps, with 2+ years focused on enterprise ML systems.
Bachelor’s/Master’s degree in Computer Science, Engineering, or a related technical field.
Proven experience with enterprise-grade platforms or large-scale SaaS applications.
Strong understanding of enterprise security and compliance requirements.
Experience with data-intensive applications and real-time processing systems.
Strong hands-on experience across cloud infrastructure, Kubernetes, CI/CD, IaC, and MLOps.
⭐ Preferred Qualifications
Experience with enterprise security frameworks and compliance standards such as SOC 2 and ISO 27001.
Experience with large-scale data processing and real-time analytics.
Strong knowledge of distributed computing, caching, and performance optimization.
Experience building REST/GraphQL APIs, microservices, and API gateways.
Experience working with enterprise clients or B2B SaaS platforms.
Exposure to finance, healthcare, government, or other compliance-heavy industries.
Understanding of GDPR, SOX, HIPAA, or similar data privacy regulations.
Experience with multi-tenant enterprise architectures.
Experience mentoring engineers and leading technical initiatives.
Strong collaboration skills across Data Science, Product, Engineering, and Enterprise Client teams.
Understanding of SLAs, business metrics, and enterprise ROI.
📈 Growth Opportunities
🚀 Progression toward Lead DevOps Engineer / Head of Infrastructure
🤖 Work with cutting-edge Enterprise AI/ML technologies
👥 Opportunity to build and lead the DevOps/Infrastructure team
🏢 Exposure to Government & MNC enterprise clients
💡 Work with modern, high-scale technology stacks
📊 Success Metrics
99.9%+ platform availability
Daily deployments with zero downtime
Improved application performance and reliability
20–30% annual infrastructure cost optimization
Zero security incidents and strong compliance adherence
Reduced deployment cycles and improved engineering velocity
95%+ enterprise client satisfaction
Improved engineering productivity and scalable infrastructure
🌟 Why Join Aaizel Tech Labs?
Be part of a forward-thinking, innovation-driven AI company.
Influence high-impact architectural decisions.
Work on mission-critical enterprise AI/ML systems.
Collaborate with a passionate and highly skilled engineering team.
Competitive compensation and a flexible working environment.
Continuous opportunities for learning and technical growth.
📩 How to Apply
If you’re an experienced DevOps/MLOps professional passionate about building reliable, scalable infrastructure for enterprise AI/ML, we’d love to hear from you!
📧 Send your resume and cover letter to:
anju@aaizeltech.com
alina@aaizeltech.com
Please mention “Senior DevOps Engineer – Gurugram” in the subject line.
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