Job Title - Decision Science Manager S&C GN
Management Level: Manager
Location: Bangalore/ Kolkata/Gurugram/Hyderabad
Must have skills: Telecom Network & Data Analytics
Good to have skills: CVM Use Case, Data Modeling, Knowledge Graph & Ontology Modeling
Job Summary:
We are seeking a skilled Network AI Manager with deep expertise in telecom networks (RAN, Core, Transport) to lead the design and delivery of AI/ML and Generative AI solutions for network operations, design & build, optimization and end-to-end automation. This role is responsible for defining the AI strategy and roadmap, translating business and network KPIs into scalable AI and agentic use cases such as anomaly detection, root cause analysis (RCA), and predictive optimization, zero touch automation, autonomous network. Candidate will provide technical and cross-functional leadership, guiding data scientists, data engineers, and network SMEs to deliver production-grade Network AI solutions.
Key Responsibilities
Project and Team Leadership
- Lead collaboration with network domain experts, business stakeholders, and product teams to identify, prioritize, and shape high-impact AI/ML and GenAI use cases across telco networks.
- Own the end-to-end Network AI delivery lifecycle, providing technical direction for the design, development, and deployment of ML and GenAI/Agentic AI solutions using large-scale structured and unstructured telecom data.
- Set standards and best practices for data analysis, feature engineering, explainability, and telecom data management to ensure reliable, and trustworthy AI systems.
- Guide the adoption of LLM-powered applications, such as GenAI copilots, knowledge assistants, and intelligent operational interfaces, to enhance network operations and decision-making and improve processes and efficiency within AI guardrails.
- Translate business and network KPIs into scalable AI architectures, roadmaps, and PoCs, ensuring alignment with enterprise design principles and long-term goals.
- Provide technical leadership and executive-level communication, advising stakeholders on AI strategy, trade-offs, and best practices for enterprise AI adoption in telecom.
- Mentor junior team members and foster a collaborative, high-performance culture and strengthen Network AI Pod.
Generative AI Expertise
- Stay up to date with emerging GenAI/Agentic AI technologies and assess their potential for solving telecom-specific challenges and define and govern solution architectures and PoCs, translating business and network requirements into scalable designs for solving telco network problems.
- Provide technical leadership and advisory support to business, network, and product stakeholders, guiding best practices for enterprise GenAI adoption within telecom environments
- Architect and oversee agentic AI workflows for network intelligence and automation, leveraging frameworks such as LangChain, LlamaIndex, AutoGen, and enterprise system integrations.
- Guide optimization of AI agents and RAG pipelines, setting standards for vector stores, performance tuning, and scalability rather than hands-on implementation.
- Advise clients on GenAI adoption, aligning solutions with business objectives and tech ecosystems.
Cloud Platform
- Familiarity with any of the cloud hyper scaler (Azure, AWS, or GCP)
- Integrate AI solutions with enterprise data ecosystems, including data lakes, warehouses, and real-time pipelines.
,
Required Qualifications
- Education: Master's or Bachelor's degree in Computer Science, Data Science, Statistics, Telecommunications, or related field.
- Experience: 12+ years of experience in Telecom Network with at least 5+ years applying AI/ML in telecom or network-related domains.
- Strong problem-solving, consulting, and stakeholder communication skills.
- Proficiency in Python, SQL.
- Strong understanding of telecom network data RAN/Core/Transport/Fiber (OSS/BSS, KPIs, alarms, logs, CDRs, performance counters).
- 4+ Years of experience of leading project delivery
- Prior experience working in consulting / client-facing roles delivering AI/ML solutions.
- Exposure to knowledge graph techniques for telecom use cases.
- Prior experience working in consulting / client-facing roles delivering AI/ML solutions.
Preferred Skills
- Experience in Data Modeling & Network 360 Design & Build.
- Experience in Knowledge Graph & Ontology for telecom use cases.
- Knowledge of semantic search and knowledge graph integration with LLMs
- Familiarity with data privacy, security, and AI governance frameworks
- Contributions to AI/ML/GenAI open-source projects or research publications.
- Familiarity with TM Forum standards (Open APIs, AI governance, ODA)
