Remote Azure data engineer Jobs – 90 Open Jobs Today

MLOps & AIOps Engineer (GCP)
TECH NEXT —Remote
- ₹70,000 - ₹90,000 a month
- Full-time
- Remote
- Azure
- Computer Science
- Master's degree
Quick apply
14d
Site Reliability Engineer
Ensono —Remote
- Remote
- Azure
- Computer Science
- DevOps
Senior Cloud Engineers
MNJ Software —Remote
- Full-time
- Remote
- Azure
- English
- Master's degree
- Work from home
Sr. Cloud Platform Engineer
Nextloop Technologies —Remote
- Remote
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Staff Engineer, AMP
MongoDB —Remote
- Remote
- Azure
- AWS
- Mentoring
Senior Technical Consultant, Platform Engineering - Azure
AHEAD —Remote
- Full-time
- Remote
- Azure
- Computer Science
- DevOps
AI Platform Engineer
AHEAD —Remote
- Remote
- Azure
- AWS
- Machine learning
- Health insurance
- Paid time off
Principal Platform Engineer
Insight Software —Remote
- Full-time
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- Azure
- DevOps
- English
Senior Platform Engineer
Insight Software —Remote
- Full-time
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- Software troubleshooting
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Senior Site Reliability Engineer
Moniepoint —Remote
- Remote
- Azure
- Java
- AWS
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Quick apply
12d
Cloud Operations - Manager
Infios —Remote
- Full-time
- Remote
- Azure
- Software troubleshooting
- DevOps
Integration Engineer
LakeFusion —Remote
- Full-time
- Remote
- Azure
- English
- SQL
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MLOps & AIOps Engineer (GCP)

TECH NEXT
Remote

Quick apply

Job details

Full-time | Contractual / Temporary
₹70,000 - ₹90,000 a month
14 days ago

Qualifications

CI/CD
Elasticsearch
Azure
Computer Science
MCP
Kubernetes
Git
Google Cloud Platform
Master's degree
Analysis skills
Docker
Bachelor's degree
Machine learning
PostgreSQL
Continuous integration
REST
Scrum
GitHub
APIs
Agile
Data science
AI
Communication skills
Python
Identity & access management

Full job description

MLOps & AIOps Engineer (GCP) | 8–9 Years |

Employment Type : Full-time / Contract

Work Mode: Remote

Experience Required: 8–9 Years (Minimum 3+ Years on Google Cloud Platform)

Job Summary

We are seeking an experienced MLOps & AIOps Engineer with strong expertise in Google Cloud Platform (GCP) to join our engineering team. The ideal candidate will be responsible for designing, deploying, and managing production-grade Machine Learning and Generative AI platforms on GCP. You will work closely with Data Scientists, Platform Engineers, and Product teams to build scalable ML pipelines, automate deployments, monitor production environments, and support AI-powered applications.

Key Responsibilities

Design, develop, and maintain scalable MLOps pipelines on Google Cloud Platform.
Build, deploy, and manage ML models using Vertex AI, including training pipelines, model registry, endpoints, and monitoring.
Develop production-grade Python applications and microservices for ML and GenAI workloads.
Implement CI/CD pipelines using GitHub Actions and automate deployment workflows.
Build and optimize RAG-based GenAI applications using LangChain and LangGraph.
Develop and manage AI/ML workflows using containerized environments on Cloud Run and GKE.
Monitor production systems, troubleshoot incidents, and provide production support for ML/GenAI applications.
Implement AIOps best practices for monitoring, observability, alerting, and incident management.
Work with vector databases and embedding pipelines to improve retrieval performance.
Collaborate with cross-functional teams to deliver secure, scalable, and highly available AI solutions.
Ensure governance, security, versioning, and release management for AI applications.

Required Technical SkillsProgramming

Strong proficiency in Python
REST APIs, Microservices, Containerization (Docker)
Performance optimization, testing, and debugging

Google Cloud Platform (Mandatory)

Vertex AI (Pipelines, Training, Model Registry, Endpoints, Monitoring)
BigQuery
Cloud Storage
Pub/Sub
Cloud Run and/or Google Kubernetes Engine (GKE)
Cloud Logging & Monitoring
IAM, Secret Manager
VPC Networking

MLOps & AI Platforms

Vertex AI (Mandatory)
Experience with Databricks, Amazon SageMaker, or Azure ML is an added advantage
Model lifecycle management
Pipeline orchestration
Automated retraining
Model monitoring and reproducibility

Generative AI (Mandatory)

LangChain
LangGraph
Retrieval-Augmented Generation (RAG)
Prompt Engineering
Tool/Function Calling
AI model evaluation techniques

Databases & Vector Stores

PostgreSQL / BigQuery
Pinecone
Weaviate
Milvus
pgvector
Elasticsearch / OpenSearch

DevOps & AIOps

GitHub Actions (CI/CD)
Git branching and release management
Docker
Kubernetes
Production Support
Monitoring & Observability
MCP Server
Apigee

Preferred Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, AI, Data Science, or a related field.
Google Cloud Professional certifications (preferred).
Strong analytical, troubleshooting, and problem-solving skills.
Excellent communication and stakeholder management skills.
Experience working in Agile/Scrum environments.

Why Join Us?

Work on cutting-edge AI, GenAI, and MLOps projects.
Opportunity to build enterprise-scale AI platforms on Google Cloud.
Collaborative engineering culture with modern DevOps and AI practices.
Exposure to the latest technologies in Vertex AI, LangChain, LangGraph, and Agentic AI.

If you're passionate about building scalable AI platforms and production-grade MLOps solutions on GCP, we'd love to hear from you!

Pay: ₹70,000.00 - ₹90,000.00 per month

Experience:

MLOps & AIOps Engineer (GCP): 8 years (Required)

Work Location: Remote

Quick apply

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