Roles and Responsibilities :

Lead (MLOps & Infrastructure Reliability) – P4

We are looking for an intelligent, resourceful, and highly skilled Lead Site Reliability Engineer to join our AIDA Engineering group. In this role, you’ll focus on architecting and maintaining cloud-

based MLOps pipelines to enable scalable, reliable, and production-grade AI/ML workflows,

working closely with AI engineers, data engineers, and software teams. You will work closely with application development teams to build scalable, containerized infrastructure to support a modern SDLC process. This group plays a critical role in ensuring the stability, reliability, and availability of mission-critical production applications across Wiley.

What we’re looking for

Up to 5 years of experience in a Site Reliability Engineering (SRE), DevOps, or

Production Engineering role, with a deep understanding of SRE principles and best practices.

Design, implement, and maintain cloud-native platforms to support AI and data workloads, with a focus on AI and data platforms such as Databricks and AWS Bedrock.

Hands-on experience with Databricks MLFlow, including model registration, versioning,

asset bundles, and model serving workflows.

Build and manage scalable data pipelines to ingest, transform,



and serve data for ML and analytics.

Proficiency in at least one coding language (Python, Go, Rust, or Typescript) for automation and debugging.

Hands-on experience in Kubernetes (K8s) for managing and orchestrating containerized applications.

Cloud experience (AWS preferred) with exposure to key services like EC2, S3, Lambda,

and Bedrock– GCP a plus.

Incident management expertise, including triaging, escalation, and resolution of high-

severity outages.

Solid troubleshooting and problem-solving skills, with experience diagnosing complex production issues.

Excellent communication skills to articulate technical challenges and solutions effectively.

Preferred skills

Experience writing, maintaining and contributing to Terraform.

Experience with AI-native Vector databases, ex. Weaviate.

Architecting and managing AI/ML workloads in production using the employing of

Job Requirements :

- 10-15 years of experience in software engineering or a related field.
- Strong expertise in AWS/GCP cloud platforms, including Terraform configuration management.
- Proficiency in Python programming language for scripting tasks such as automation testing.

📌 Lead MLOps Engineer / Site Reliability Engineer – AI/ML Infrastructure (Hyderabad)
🏢 Virtusa
📍 Hyderabad