Principle Engineer

Job Description

You will manage a talented team of data scientists and AI engineers, driving the adoption of intelligent automation, predictive analytics, and proactive problem resolution across our complex IT landscape. This position requires a leader with a deep understanding of both data science principles and the intricacies of enterprise IT operations.

Responsibilities

• Strategic Leadership : Define and execute the AIOps strategy and roadmap, aligning it with overall IT and business objectives. Identify opportunities to leverage AI / ML for enhanced IT observability, incident management, performance optimization, and automation.
• Team Management & Development : Lead, mentor, and grow a high-performing team of data scientists and AI engineers. Foster a culture of innovation, continuous learning, and technical excellence.
• Solution Design & Development : Oversee the end-to-end design, development, and deployment of AIOps solutions, including anomaly detection, predictive failure analysis, root cause analysis, intelligent alerting, and automated remediation.
• Cross-Functional Collaboration : Partner closely with IT Operations, Site Reliability Engineering (SRE), Network Engineering, Application Development, and other stakeholders to understand operational challenges and deliver impactful AI-driven solutions.
• Data & Platform Management : Ensure the availability, quality, and governance of operational data necessary for AI / ML model training and inference. Drive the selection, integration, and optimization of AIOps platforms and tools.
• Model Lifecycle Management : Establish robust MLOps practices for model development, testing, deployment, monitoring, and retraining to ensure the continuous effectiveness and reliability of AI models in production.
• Innovation & Research : Stay abreast of the latest advancements in AI / ML, AIOps, and IT operations. Drive research and experimentation to explore new techniques and technologies that can further enhance our operational intelligence.
• Performance & Metrics : Define key performance indicators (KPIs) for AIOps initiatives and regularly report on the impact and value delivered to the organization.
• Budget & Resource Management : Manage project budgets, resources, and timelines effectively to ensure successful delivery of AIOps programs.

Qualifications

Required Qualifications :

Preferred Qualifications :

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Skills Required

Java, Ml, Servicenow, Hadoop, Scala, Ai, Kafka, Elk Stack, Datadog, Data Science, Gcp, MLops, Docker, Spark, Dynatrace, Splunk, Azure, Kubernetes, Python, Aws