Solution Architect - AIops / MLops / Dataops Citiustech

11.0 - 20.0 years

40 - 50 Lacs

Pune, Chennai, Bengaluru

Hybrid

Senior xOps Specialist AIOps, MLOps & DataOps Architect Location: Chennai, Pune Employment Type: Fulltime - Hybrid Experience Required: 12-15 years Job Summary: We are seeking a Senior xOps Specialist to architect, implement, and optimize AI-driven operational frameworks across AIOps, MLOps, and DataOps. The ideal candidate will design and enhance intelligent automation, predictive analytics, and resilient pipelines for large-scale data engineering, AI/ML deployments, and IT operations. This role requires deep expertise in AI/ML automation, data-driven DevOps strategies, observability frameworks, and cloud-native orchestration. Key Responsibilities – Design & Architecture AIOps: AI-Driven IT Operations & Automation Architect AI-powered observability platforms, ensuring predictive incident detection and autonomous IT operations. Implement AI-driven root cause analysis (RCA) for proactive issue resolution and performance optimization. Design self-healing infrastructures leveraging machine learning models for anomaly detection and remediation workflows. Establish event-driven automation strategies, enabling autonomous infrastructure scaling and resilience engineering. MLOps: Machine Learning Lifecycle Optimization Architect end-to-end MLOps pipelines, ensuring automated model training, validation, deployment, and monitoring. Design CI/CD pipelines for ML models, embedding drift detection, continuous optimization, and model explainability. Implement feature engineering pipelines, leveraging data versioning, reproducibility, and intelligent retraining techniques. Ensure secure and scalable AI/ML environments, optimizing GPU-accelerated processing and cloud-native model serving. DataOps: Scalable Data Engineering & Pipelines Architect data processing frameworks, ensuring high-performance, real-time ingestion, transformation, and analytics. Build data observability platforms, enabling automated anomaly detection, data lineage tracking, and schema evolution. Design self-optimizing ETL pipelines, leveraging AI-driven workflows for data enrichment and transformation. Implement governance frameworks, ensuring data quality, security, and compliance with enterprise standards. Automation & API Integration Develop Python or Go-based automation scripts for AI model orchestration, data pipeline optimization, and IT workflows. Architect event-driven xOps frameworks, enabling intelligent orchestration for real-time workload management. Implement AI-powered recommendations, optimizing resource allocation, cost efficiency, and performance benchmarking. Cloud-Native & DevOps Integration Embed AI/ML observability principles within DevOps pipelines, ensuring continuous monitoring and retraining cycles. Architect cloud-native solutions optimized for Kubernetes, containerized environments, and scalable AI workloads. Establish AIOps-driven cloud infrastructure strategies, automating incident response and operational intelligence. Qualifications & Skills – xOps Expertise Deep expertise in AIOps, MLOps, and DataOps, designing AI-driven operational frameworks. Proficiency in automation scripting, leveraging Python, Go, and AI/ML orchestration tools. Strong knowledge of AI observability, ensuring resilient IT operations and predictive analytics. Extensive experience in cloud-native architectures, Kubernetes orchestration, and serverless AI workloads. Ability to troubleshoot complex AI/ML pipelines, ensuring optimal model performance and data integrity. Preferred Certifications (Optional): AWS Certified Machine Learning Specialist Google Cloud Professional Data Engineer Kubernetes Certified Administrator (CKA) DevOps Automation & AIOps Certification

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