MLOps & AIOps Engineer (GCP)

Job Title : MLOps & AIOps Engineer (GCP) Employment Type : Full-time / Contract (C2C) Experience : 8-9 Years Work Mode : Hybrid

Job Summary

You will work closely with Data Scientists, Platform Engineers, and Product Teams to operationalize AI and GenAI use cases while ensuring high availability, automation, monitoring, and performance optimization.

Key Responsibilities

- Design and develop scalable MLOps solutions on Google Cloud Platform.
- Build, deploy, and manage ML and Generative AI workloads using Vertex AI.
- Develop and maintain automated CI/CD pipelines using GitHub Actions.
- Deploy, monitor, and optimize machine learning models in production.
- Implement model monitoring, automated retraining, and performance tracking.
- Collaborate with cross-functional teams to operationalize AI and GenAI solutions.
- Build and maintain Agentic AI workflows using LangChain and LangGraph.
- Implement monitoring, logging, security, and observability best practices.
- Troubleshoot production issues and ensure platform reliability.

Required SkillsProgramming

- Python
- REST APIs
- Microservices
- Containerization

Google Cloud Platform

- Vertex AI
- Cloud Storage
- BigQuery
- Pub/Sub
- Cloud Run
- GKE
- IAM
- Secret Manager
- Cloud Logging & Monitoring
- VPC Networking

MLOps

- ML Pipeline Orchestration
- Model Deployment
- Model Registry
- Model Monitoring
- Automated Retraining




- ML Lifecycle Management

Generative AI

- LangChain
- LangGraph
- Retrieval-Augmented Generation (RAG)
- Prompt Engineering
- Tool/Function Calling
- AI Model Evaluation

Databases / Vector Stores

Experience with one or more of the following:

- Pinecone
- Weaviate
- Milvus
- pgvector
- Elasticsearch
- OpenSearch

DevOps

- GitHub Actions
- GitHub CI/CD
- Release Management
- Branching Strategies

Required Experience

- 8+ years of overall IT experience.
- Minimum 3+ years of hands-on experience with Google Cloud Platform (GCP).
- Strong experience in designing and implementing enterprise MLOps solutions.
- Experience working with Vertex AI or other ML platforms such as SageMaker, Databricks, or Azure ML.
- Hands-on experience with GitHub CI/CD and DevOps practices.
- Good understanding of AI Ops concepts.
- Knowledge of MCP Server and Apigee.
- Experience in GenAI release management and production deployments.

Preferred Qualifications

- Robust understanding of cloud security and infrastructure best practices.
- Excellent analytical, troubleshooting, and communication skills.
- Ability to work in a collaborative Agile environment.

Pay: ₹80,000.00 - ₹90,000.00 per month

Experience :

- overall IT experience.: 8 years (required)
- Google Cloud Platform (GCP): 3 years (required)

Work Location: Hybrid remote in Noida, Uttar Pradesh

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