We are seeking an experienced AI/ML Engineer to design and implement intelligent systems that reason over complex, structured data to drive deterministic decisions, root-cause diagnosis, asset and service intelligence, and workflow automation across large-scale environments. The engineer will be responsible for developing end-to-end AI solutions, including data modeling, ML/LLM development, APIs, and integrations to enhance accuracy, observability, and automation in IT workflows. Key Responsibilities: - Design hybrid AI/ML systems combining rule-based logic with machine learning to evaluate structured inputs and provide deterministic outcomes. - Build reasoning engines for dependency tracing, failure point identification, and diagnostic summaries. - Develop models to detect conflicts, anomalies, and misconfigurations in large-scale datasets. - Model relationships between endpoints, services, dependencies, and cloud assets using graph-based approaches. - Correlate telemetry and governance data to assess health patterns and support compliance goals. - Create APIs and assistant-style interfaces for real-time workflows in ITSM platforms. - Implement explainability layers for decision justifications tailored to technical/non-technical stakeholders. Must-Have Skills & Experience: - 3–5+ years of hands-on AI/ML engineering experience with strong Python skills. - Proven expertise in building production-grade AI systems combining rule-based logic with ML. - Experience working with structured/semi-structured datasets like policies or service maps.