▷ [Immediate Start] Senior DevOps Engineer / MLOps Specialist

Position : Senior DevOps Engineer / MLOps Specialist – AI Platforms

Location : Hyderabad, India (Full-time work from office)

Experience Required : 7+ Years (DevOps, Cloud Infrastructure, and MLOps exposure

preferred)

Employment Type : Full-Time

Role Overview

We are seeking a Senior DevOps Engineer to lead DevOps and MLOps initiatives for

QMentisAI, QualiZeal’s enterprise-grade Generative AI platform for quality engineering, and

NexaAI, QualiZeal’s service offering for developing GenAI-based solutions. This role

requires deep expertise in cloud automation, CI / CD orchestration, infrastructure scaling,

and AI / ML pipeline enablement.

The ideal candidate is a strategic technologist with hands-on experience across multiple

DevOps ecosystems, including Azure, AWS, and GCP, and a strong grasp of MLOps

practices for model lifecycle management, data versioning, and automated deployment.

Key Responsibilities

• DevOps Leadership & Automation

o Architect, implement, and maintain CI / CD pipelines across multi-cloud

environments (Azure, AWS, GCP).

o Drive Infrastructure-as-Code (IaC) using Terraform, Helm, and cloud-native

tools.

o Manage containerized workloads, orchestration (Kubernetes, Docker

Swarm), and API gateway integrations.

o Collaborate with AI / ML engineers to operationalize machine learning models.

o Implement model registry, automated testing, deployment, and monitoring

pipelines.

o Enable data versioning and reproducibility using MLflow, DVC, or equivalent

tools.

o Design highly available, fault-tolerant architectures for GenAI workloads.

o Lead cloud migration, cost optimization, and zero-downtime deployments.

o Enforce best practices for security, compliance, and performance

monitoring.

o Partner with AI Architects and Platform Teams to align DevOps / MLOps

frameworks with QualiZeal’s AI roadmap.

o Mentor junior DevOps engineers within AICoE and standardize automation

practices.

o Represent DevOps at project reviews, ensuring scalable and maintainable

delivery pipelines.

Required Skills & Qualifications

o 7+ years of experience in DevOps, CI / CD automation, and cloud

infrastructure management.

o Strong proficiency in Azure, AWS, or GCP DevOps ecosystems.

o Experience in Docker, Kubernetes, Helm, Terraform, Jenkins, and GitOps

workflows.

o Working knowledge of AI / ML platforms and MLOps lifecycle.

o Familiarity with Python scripting, REST APIs, and container security.

o Excellent analytical and troubleshooting skills.

o Strong communication and collaboration across multidisciplinary teams.

o Ability to lead DevOps strategies and align cloud architectures with AI

engineering goals.

Preferred Qualifications

What We Offer

Engineering.