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
