Posted:1 day ago|
Platform:
On-site
Full Time
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.
• MLOps Enablement
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.
• Cloud Infrastructure & Security
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.
• Collaboration & Mentorship
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
• Technical Expertise
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.
• Professional Attributes
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
• Hands-on with MLflow, Kubeflow, Azure Machine Learning, or Vertex AI.
• Experience integrating LLM workflows with CI/CD pipelines.
• Knowledge of monitoring tools (Prometheus, Grafana, ELK, Datadog).
• Familiarity with RAG and data management pipelines in GenAI environments.
What We Offer
• Be at the heart of DevOps evolution for our AI services and products.
• Work on cloud-native, AI-integrated infrastructures that define modern Quality
Engineering.
• Join a team that values innovation, autonomy, and technical mastery.
• Competitive compensation, benefits, and leadership growth opportunities.
QualiZeal
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