Senior AI/ML Engineer – Service Assurance

Role overview

Senior AI/ML Engineer – Service Assurance at Orange Business

You will be responsible for exploring service and network data, designing and implementing AI/ML and agentic capabilities on top of Splunk and Ciena Blue Planet UAA, and industrializing these solutions into production-grade features.

Responsibilities

• Design and Implement AI/ML Solutions:Own the end-to-end lifecycle of AI/ML models for service assurance, covering anomaly detection, event correlation, root cause analysis, and capacity/traffic forecasting.
• Implement MLOps Best Practices:Ensure our solutions are production-grade by implementing model versioning, automated testing, CI/CD for ML, and continuous monitoring for data and model drift.
• Deliver Reusable Capabilities:Expose AI/ML and agentic features as well-documented, reusable components that integrate seamlessly into dashboards, alerts, and operational workflows. 3-Strategy & Collaboration.

Required qualifications

• Required Skills and Experience. 1- Core Technical Skills.
• 5+ years in software and/or ML engineering, with at least 3 years of hands-on experience building and deploying production AI/ML models.
• Programming: Strong proficiency in Python and its standard data science/ML libraries (e.g., Pandas, Scikit-learn, TensorFlow/PyTorch).
• Ability to write clean, testable, production-ready code.
• Data Engineering: Solid ExperiencewithSQL and at leastonedistributed dataprocessing framework(e.g., Spark, Flink) tohandlelarge-scale datasets.
• MLOps:Hands-on experience with MLOps tooling and methodologies (e.g., MLflow for versioning, CI/CD for model deployment, monitoring for drift). 2-AI/ML Expertise.
• Machine Learning Foundations: Solid understanding of ML algorithms (especially for anomaly detection, classification, and time-series forecasting) and the ability to choose the right tool for the job.
• Feature Engineering: Proven ability to explore diverse data sources (logs, metrics, events, topology), assess data quality, and derive meaningful features.
• Agentic AI Concepts: A strong interest in and understanding of agentic AI concepts (LLM-based agents, tool-calling, reasoning) and a drive to apply them to real-world operational problems.
• Observability/AIOps Platforms: Familiarity with platforms like Splunk, ELK, or Prometheus for analyzing logs, metrics, and alerts. 3-Professional & Strategic Skills.
• Problem Solving & Communication: Strong analytical skills to translate complex operational problems into concrete technical solutions.
• Ability to communicate effectively with both technical and non-technical stakeholders.
• Master’s degree in Computer Science, Data Science, or a related field, or equivalent practical experience.
• Nice-to-Have Skills.
• Experience with Splunk or equivalent observability tooling in a telecom/IT operations context.
• Exposure to service assurance or network operations concepts (e.g., alarms, incidents, SLAs, topology, OSS/BSS).
• You bring rigor, passion for challenges, and determination.
• You seek the opportunity to expand your expertise, achieve your goals, and thrive.
• Global Opportunities: Work in multi-national teams with opportunity to collaborate with colleagues and customers from all over the world.
• Flexible Work Environment: Flexible working hours and possibility to combine work from office and home (hybrid ways of working).
• Professional Development: training programs and upskilling/re-skilling opportunities.
• Career Growth: Internal growth and mobility opportunities within Orange.
• Caring and Daring Culture: Health and well-being programs and benefits, diversity & inclusion initiatives, CSR and employee connect events.
• Reward Programs: Employee Referral Program, Change Maker Awards.
• At Orange, only your skills matter.
• Regardless of your age, gender, background, origin, religion, sexual orientation, disability, neurodiversity, or appearance, we actively encourage diversity within our teams, as it is a collective strength and a driver of innovation.
• Orange is a disability-inclusive employer: please feel free to let us know about any specific needs you may have.

Employment details

• Location: GURGAON [HARYANA] [INDIA], GURGAON [INDIA]

About the employer

• Join us at Orange Business!

Additional role details

• Publication date : Apr 27, 2026, 12:00AM.
• We are a network and digital integrator that understands the entire value chain of the digital world, freeing our customers to focus on the strategic initiatives that shape their business.
• Every day, you will collaborate with a team dedicated to providing consistent, sustainable global solutions, no matter where our customers operate.
• With over 30,000 employees across Asia, the Americas, Africa, and Europe, we offer a dynamic environment to develop and perfect your skills in a field filled with exciting challenges and opportunities.
• As a Senior AI/ML Engineer, you will be at the heart of transforming our Service Assurance capabilities.
• Your mission will include (and not be limited to) leverage cutting-edge AI to predict and prevent service disruptions, automate root cause analysis, and ensure our network runs with unparalleled reliability.
• This role combines hands-on data exploration, model development, and solid software engineering to deliver advanced analytics for anomaly detection, event correlation, root cause analysis, and forecasting.
• Key Responsibilities. 1-Core Model Development & Innovation.
• This includes data discovery, feature engineering, model training, evaluation, and deployment.
• Prototype and Industrialize Agentic AI:Explore and build next-generation operational tools, such as LLM-based copilots for triage, agents that reason over telemetry and topology, and natural-language interfaces for observability data.
• Stay at the Forefront of AIOps:Continuously research advances in ML for observability, proactively prototyping and industrializing innovative ideas that enhance our service-assurance capabilities. 2-Engineering & MLOps Excellence.
• Build Scalable Data Pipelines:Engineer and maintain robust pipelines to ingest, transform, and prepare high-volume observability data (metrics, logs, alarms, tickets, topology) for AI/ML workloads.
• Translate Business Needs into AI Use Cases:Collaborate closely with the AI lead and service-assurance stakeholders to understand operational challenges and define high-impact AI/ML projects.
• Measure and Communicate Impact:Quantify the business value of your solutions (e.g., MTTR reduction, alarm noise reduction) and effectively communicate results and trade-offs to technical and non-technical partners.