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Tier-1 brand, mid-level AI/devops role in a metro increases applicant competition.
Combines ML engineering and enterprise infrastructure experience, moderately limiting cross-industry transfers.
Multiple mandatory technical skills and a 5+ years requirement enforce strict shortlisting filters.
Design, build, and deploy AI-driven automation solutions to reduce manual effort in Linux/Unix Hybrid Cloud Infrastructure server environments.
Develop intelligent workflows for incident detection, root cause analysis, remediation, and operational runbook automation.
Collaborate with engineering and operations teams to integrate AI capabilities, ensure scalable reusable automation frameworks, and evaluate emerging AI technologies for operational efficiency.
5+ years of software engineering experience with demonstrable AI engineering skills.
Strong programming skills in Python and Bash; SQL desirable.
Experience with containerization (Kubernetes, Docker), Infrastructure-as-Code, CI/CD pipelines, AI/ML frameworks (PyTorch, TensorFlow), and cloud platforms (preferably GCP).
Work Experience Required: 5+ years in relevant domains.
Experienced in building AI-driven automation or AIOps solutions in infrastructure or server environments, particularly enterprise-scale Linux/Unix.
Comfortable working within established architecture and strategy focusing on operational task automation and tooling improvements.
Skilled at applying AI/ML lifecycle knowledge and emerging GenAI technologies (e.g., automation agents, LLM-based recommendation systems) to enhance operational workflows and incident management.