Position Overview

The AI Observability Engineer will be instrumental in implementation of scalable, cloud-native solutions to meet the growing needs of our Data & Development team. The successful candidate will demonstrate the ability to abstract complexity and create reusable, scalable patterns that accelerate development. The AI Observability Engineer will build and maintain a robust framework to ensure the reliability and maintainability of DPR Construction's complex AI systems.

Responsibilities
Standardize observability practices across AI/ML and other development teams including logging, metrics, tracing, and model performance monitoring, ingesting data from multiple platforms
Lead hands-on implementation of automation-first DevOps and MLOps practices, enabling infrastructure-as-code and consistent, repeatable setting provisioning
Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly detection
Deploy, maintain and monitor containerized ML workloads
Extend existing CI/CD pipelines to support automated infrastructure changes and ML workflows
Implement AI-driven data validation, schema and concept drift detection and metadata management.
Establish governance frameworks for AI systems, including bias detection,



explainability, and auditability
Extend existing Azure RBAC strategy by automating role and permission management to reduce manual intervention
Develop automated test suites for model performance, regression, edge cases and bias validation
Monitor model KPIs (accuracy, precision, recall, latency, calibration)
Ensure reproducability of experiments and production models
Act as a technical point of contact for DevOps and MLOps practices, developing reusable patterns, documentation, and proof-of-concepts to drive adoption

Qualifications
Bachelor’s degree in computer science, Data Science, Information Systems, or a related field
5+ years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering
Solid understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure
Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn

Skills:- Data Science, DevOps, MLOps, Data engineering, TensorFlow, PyTorch, Scikit-Learn, CI/CD and Azure

📌 Ai/ml Engineer Ai Observability Ml Ops Engineer Pune
🏢 TalentOne HR Consulting
📍 Pune