Senior AIOps Engineer

This is a fully remote position, open to applicants in India.

📋 Description

• Take ownership of production reliability for AI/ML services.

• Establish and uphold SLOs/SLIs for essential AI systems.

• Enhance and develop AI observability.

• Work alongside data scientists and ML engineers to optimize deployment workflows for models.

• Provision, deploy, configure, and sustain new components of AI infrastructure.

• Reduce costs associated with LLMs.

• Engage in an on-call rotation for AI/ML systems.

• Collaborate across various disciplines.

• Create and maintain production-quality services and tools using Python.

⛳️ Requirements

• Bachelor's degree in Computer Science, Engineering, or a related discipline (Master's degree is preferred).

• Over 4 years of professional software engineering experience, including at least 3 years in commercial software engineering or production operations (SRE/DevOps/Platform/ML platform), managing services on Kubernetes and/or major cloud platforms.

• Strong experience with GCP is preferred, including practical knowledge of: GKE (Kubernetes Engine), BigQuery (data warehousing, SQL, schema management), Pub/Sub (event messaging), Vertex AI (batch prediction, model deployment), Cloud SQL, GCS, and IAM.

• Experience in operating production systems at scale, ideally with distributed, microservices- or Kubernetes-based architectures.

• Practical experience with CI/CD tools and deployment automation (GitLab CI/CD, GitHub Actions, or similar).

• Understanding of fundamental machine learning concepts and model lifecycles (training, evaluation, deployment, monitoring), as well as familiarity with common ML tools.

• Familiarity with LLM ecosystem tools — AI gateways, vector databases, RAG pipelines, embedding models, or LLM evaluation frameworks — is a significant advantage.

🏝️ Benefits

• Medical insurance.

• Accident insurance.

• Retiral benefits.

• 12 company-paid holidays.

• 2 flexible holidays.

• Privilege/earned leave.

• Casual/sick leave.

• Paid maternity and paternity leaves.

• Weekly wellness events.