AI/Data Science Eng I

Role & responsibilities

JOB DESCRIPTION

• Participate in a global team of AIOps Architects, Platform Engineers, Automation Engineers, and IT Operations teams.
• Automate the provisioning, configuration, and lifecycle management of LLM runtimes, embedding pipelines, vector databases, and knowledge ingestion services.
• Deploy and manage LLM configurations, embedding models, prompt templates, runtime parameters, patching, and platform tools across environments using Ansible playbooks.
• Integrate ITSM and Service Catalog platforms (ServiceNow / First) with Terraform and Ansible to automate AI platform service requests and approvals
• Provision and operate LLM, vector, and ingestion workloads on Kubernetes platforms (e.g., Tanzu, EKS, or equivalent) using IaC practices.
• Utilize monitoring and observability tools to track performance, availability, and health of AI platforms, including SolarWinds, Prometheus, Grafana, CloudWatch (where applicable), and custom scripts.
• Support enterprise-grade backup, recovery, retention, and purge strategies for vector data, metadata, and platform configurations.
• Collaborate with IT, Security, and Business partners to continuously improve platform reliability, scalability, performance, governance, and audit readiness.
• Demonstrate strong ownership, willingness to learn, and continuous improvement while supporting AI, automation, and AIOps technologies in an enterprise environment.

Preferred candidate profile

• Bachelors degree in computer science, Engineering, or a related technical discipline. Minimum of 6–8 years of experience as a Platform Engineer, AIOps Engineer, AI/ML Operations Engineer, or Automation Engineer supporting enterprise platforms.
• Strong 3+ years of experience with LLM platforms, embeddings, vector & graph databases, prompt management, and ingestion pipelines in production environments.
• Minimum of 2-3 years of experience with Git-based repositories and CI/CD platforms, preferably GitLab or GitHub, for controlled deployments and versioning.
• Solid understanding of Linux (RHEL), automation scripting, platform security, monitoring, and enterprise governance practices.
• Knowledge of Identity and Access Management (IAM) and secrets management solutions such as CyberArk, HashiCorp Vault, or enterprise Secrets Managers.