Gen AI Architect , AI architect ,

Job Title: Gen AI Engineer
Position: Software Engineer
Experience: 5 - 8 Years
Position ID: J0526-0788
Category: Software Development
Shift: General Shift
Work Mode: Work from office all 5 Days
Primary location: Chennai, India
CGI Office: DLF Chennai
Client location: Kandanchavady, Old Mahabalipuram Road, Chennai
Employment Type: Full Time
Education : BE/B.tech/ME/M.Tech


Required qualifications to be successful in this role
Position Description:

We are looking for an experienced GEN AI Engineer with strong Telecom Network domain expertise to drive intelligent automation and analytics across network operations. The role focuses on applying AI/ML techniques to OSS platforms (e.g., NetAct), RAN/Core networks, and network data to improve performance, reliability, and operational efficiency.
The ideal candidate should have a blend of AI/ML capabilities, telecom domain understanding, and data engineering exposure, with the ability to convert business/network problems into scalable AI solutions.
Analyse existing applications and systems to identify opportunities for AI-driven enhancements, and drive AI-led innovation by proposing high-impact use cases to improve operational efficiency, automation, and overall system performance.

Key Responsibilities :

1. AI/ML Solution Development for Telecom

. Design and implement AI/ML models for telecom use cases such as


1. Network anomaly detection
2. Fault prediction and root cause analysis
3. Traffic forecasting and capacity optimization
4. Predictive maintenance


. Work with structured and unstructured network data (KPIs, alarms, logs, performance metrics)

2. Telecom Domain Integration (OSS / RAN / Core)

1. Work closely with OSS platforms (e.g., NetAct), SON, and network management systems
2. Understand RAN/Core network architecture and integrate AI models into operational workflows
3. Translate network-level challenges into data-driven solutions

3. AI-Driven Automation & AIOps

. Implement AIOps capabilities for:
. Enable closed-loop automation using AI insights

4. Data Engineering & Pipeline Development

. Build and manage data pipelines for ingesting telecom data from multiple sources
. Work with big data technologies (e.g., Spark, Kafka, Hadoop – preferred)
. Ensure data quality, preprocessing, and feature engineering

5. AI Integration in DevOps / CI-CD

. Integrate AI models into CI/CD pipelines for continuous deployment and monitoring
. Enable model lifecycle management (MLOps)
. Work with containerized environments (Docker, Kubernetes)

6. Stakeholder Collaboration

. Collaborate with:
. Participate in use case identification, solution design, and implementation discussions

7. Governance, Security & Compliance

. Ensure compliance with data privacy, security, and telecom regulations
. Implement best practices for model governance and explainability

Must-Have Skills :

AI / ML

. Strong experience in Machine Learning / Deep Learning
. Hands-on with Python (NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch)
. Experience in time-series analysis, anomaly detection, predictive modeling

Telecom Domain

. Strong understanding of:
. Hands-on exposure to OSS tools (e.g., NetAct, SON, EMS/NMS) is a strong advantage

Data & Platforms

. Experience with:
. Understanding of data pipelines and ETL processes

DevOps / Cloud

. Exposure to:
. Understanding of MLOps concepts

Good-to-Have Skills

. Experience with AIOps platforms or observability tools
. Knowledge of 5G / ORAN ecosystems
. Exposure to GenAI use cases (log analysis, RCA, automation assistants)
. Familiarity with cloud platforms (AWS/Azure/GCP)
. Understanding of network automation frameworks

Soft Skills

. Strong analytical and problem-solving mindset
. Ability to work in cross-functional and global teams
. Effective communication with both technical and business stakeholders
. Proactive and ownership-driven approach

Key Success Metrics

. Reduction in network incidents and MTTR
. Improved prediction accuracy and model performance
. Increased automation in network operations
. Faster issue detection and resolution
. Business impact through AI-driven insights