Lead MLOps Engineer (Gen AI)

Idfc First Bank Limited; Bengaluru; On-site; INR 4,500,000 - 6,000,000; Full time

Job summary

Idfc First Bank Limited in Bengaluru is seeking a Lead MLOps Engineer to design and scale the infrastructure powering enterprise ML and GenAI applications. This hands-on leadership role owns end-to-end MLOps pipelines, from training to production.

You will guide a small engineering team, work across cloud and on‑prem environments (AWS/Azure/GCP and on‑prem), and collaborate with data scientists and backend teams to move models from experimentation to production.

Qualifications

• 8+ years of experience in MLOps/DevOps/Cloud Infrastructure.
• Strong Kubernetes and Docker production expertise.
• Experience deploying ML/GenAI workloads across cloud and on‑prem.
• Deep understanding of ML training, inference, and model lifecycle.
• Experience with self-hosted LLMs/GenAI in enterprises.
• Hands-on with Kubeflow, ONNX, Kong, JFrog, or similar.
• Proficient in CI/CD, infrastructure automation, monitoring, security, and HA.
• Strong stakeholder management and collaboration skills.
• BE/BTech/MTech/MCA or equivalent technical qualification.

Responsibilities

• Design and build scalable MLOps pipelines for training, deployment, and lifecycle management.
• Build infrastructure for self-hosted LLMs and GenAI across cloud and on‑prem.
• Own Kubernetes-based orchestration, containerization, and production deployment.
• Manage infrastructure across AWS, Azure, GCP and on‑prem environments.
• Build and improve CI/CD, model deployment, automation and release pipelines.
• Set up monitoring for model performance, infrastructure health, latency, availability and resource utilisation.
• Drive infrastructure scalability, capacity planning, reliability, security and cost optimisation.
• Work with platforms/tools such as Kubeflow, ONNX, Kong and JFrog.
• Partner closely with Data Scientists, AI Engineers, Data Engineers and Backend teams to move models from experimentation to production.
• Lead and mentor MLOps/DevOps engineers while remaining technically hands-on.

Skills

MLOps

DevOps

Leadership

Stakeholder management

Cloud infrastructure

Education

BE / BTech / MCA or equivalent

MTech

Tools

Kubernetes

Docker

Kubeflow

ONNX

Kong

JFrog

CI/CD tooling

Job description

We are looking for a Lead MLOps Engineer to build and scale the infrastructure powering enterprise ML and GenAI applications. The role will own the end-to-end MLOps ecosystem, from model training and deployment pipelines to Kubernetes, cloud/on-prem infrastructure, self-hosted LLMs, monitoring, security and production reliability.

This is a hands-on technical leadership role requiring strong experience across MLOps, DevOps and enterprise infrastructure, along with the ability to lead a small engineering team.

Responsibilities:

• Design and build scalable MLOps pipelines for training, deployment and lifecycle management of ML/GenAI models.
• Build infrastructure for self-hosted LLMs and GenAI applications across cloud and on-prem environments.
• OwnKubernetes-based orchestration, containerization and production deployment of ML workloads.
• Manage infrastructure across AWS, Azure, GCP and on-prem environments.
• Build and improveCI/CD, model deployment, automation and release pipelines.
• Set up monitoring for model performance, infrastructure health, latency, availability and resource utilisation.
• Drive infrastructure scalability, capacity planning, reliability, security and cost optimisation.
• Work with platforms/tools such as Kubeflow, ONNX, Docker, Kubernetes, Kong and JFrog.
• Partner closely with Data Scientists, AI Engineers, Data Engineers and Backend teams to move models from experimentation to production.
• Lead and mentor MLOps/DevOps engineers while remaining technically hands-on.

Requirements:

• 8+ years of overall experience with strong hands-on exposure to MLOps / DevOps / Cloud Infrastructure.
• Strong expertise in Kubernetes and Docker in production environments.
• Experience deploying ML/GenAI workloads across AWS, Azure, GCP and/or on-prem infrastructure.
• Strong understanding of ML training and inference infrastructure, deployment pipelines and production model lifecycle.
• Experience supportingself-hosted LLMs / GenAI modelsin enterprise environments.
• Hands-on experience with tools such as Kubeflow, ONNX, Kong, JFrog, or similar platforms.
• Strong understanding ofCI/CD, infrastructure automation, monitoring, security and high availability.
• Experience leading MLOps / DevOps engineers and owning large-scale production deployments.
• Strong stakeholder management and collaboration skills.
• B. E. / B. Tech / M. Tech / MCA or equivalent technical qualification.

Preferred:

• Experience working in Banking / FinTech or other large-scale enterprise environments.
• Experience managing systems spanning both cloud and on-prem infrastructure.
• Exposure to production GenAI platforms, LLM inference infrastructure and GPU-based workloads.