Senior Engineer, MLOps

Senior Engineer MLOps

Location: Bangalore (Hybrid)

Experience: 6–10 Years

Job Summary

We are looking for a highly skilled Senior Engineer – MLOps to build, deploy, and operate scalable, reliable AI/ML infrastructure that powers our next-generation AI platforms. This role sits at the intersection of Machine Learning, DevOps, and Cloud Engineering, with a strong focus on supporting LLM agent systems, data pipelines, cloud infrastructure, and production AI workloads.

The ideal candidate will have hands-on experience deploying and managing machine learning systems in cloud environments, automating infrastructure, building CI/CD pipelines, and ensuring the performance, scalability, and reliability of AI/ML platforms.

Key Responsibilities

• Design, deploy, and manage scalable AI/ML infrastructure for production environments.
• Build and maintain infrastructure supporting LLM agent systems, machine learning models, and data pipelines.
• Deploy and operate ML/AI workloads across major cloud platforms such as AWS, GCP, or Azure.
• Develop and maintain containerized applications using Docker and serverless container platforms such as Cloud Run, ECS Fargate, or Azure Container Apps.
• Design and manage cloud databases, data warehouses, and storage solutions for AI applications.
• Build and optimize ETL/ELT pipelines to support machine learning workflows and analytics.
• Implement Infrastructure as Code (IaC) using Terraform or similar tools.
• Design and maintain CI/CD pipelines for automated model deployment and infrastructure provisioning.
• Implement monitoring, logging, alerting, and performance optimization for AI/ML systems.
• Manage event-driven architectures using messaging platforms such as Kafka, Pub/Sub, SNS/SQS, or similar technologies.
• Collaborate closely with AI/ML Engineers, Data Scientists, and Software Engineers to support model deployment and production operations.
• Optimize infrastructure for reliability, scalability, latency, and cost efficiency.
• Ensure security, governance, and operational best practices across cloud environments.

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 6–10 years of experience in MLOps, DevOps, Cloud Engineering, or Infrastructure Engineering.
• Proven experience deploying and operating Machine Learning or AI systems in production.
• Strong expertise in cloud platforms including Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure.
• Experience with Infrastructure as Code (Terraform preferred).
• Strong Python programming skills.
• Excellent analytical, troubleshooting, and problem-solving skills.
• Strong communication skills with the ability to collaborate across technical and non-technical teams.

Required Technical Skills

• Expert-level Python or Typescript
• Very deep experience with at least one major cloud platform

Including microservice creation and maintenance

Including databases and warehousing

Including messaging/streaming infrastructure

• Strong experience with containerization
• Strong experience with building-out telemetry and monitoring platforms
• Strong experience with ML model serving
• Expertise with infrastructure as code (IaC) such as Terraform
• Experience building and maintaining CI/CD pipelines
• Experience both implementing and advocating for MLOps best practices, model lifecycle management, and AI platform operations.
• Knowledge of:

Vector Databases

Agent Orchestration

Cost Optimization

Preferred Skills

• Experience with LLM Agent Frameworks such as Google ADK, LangChain, LangGraph, or similar.
• Experience operating LLM/Generative AI workloads in production.

Preferred Candidate Profile

• Experience supporting enterprise-scale AI/ML platforms.
• Passion for building reliable, scalable, and automated infrastructure.
• Ability to troubleshoot complex distributed systems.
• Strong collaboration and stakeholder management skills.
• Self-driven with a continuous learning mindset and enthusiasm for emerging AI technologies.