AGM - IT Analytics

Job Req ID: 49969

Location:
Pune, Maharashtra, IN

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Function: Other

About:
Vodafone Idea Limited is an Aditya Birla Group and Vodafone Group partnership. It is India’s leading telecom service provider. The Company provides pan India Voice and Data services across 2G, 3G and 4G platform. With the large spectrum portfolio to support the growing demand for data and voice, the company is committed to deliver delightful customer experiences and contribute towards creating a truly ‘Digital India’ by enabling millions of citizens to connect and build a better tomorrow. The Company is developing infrastructure to introduce newer and smarter technologies, making both retail and enterprise customers future ready with innovative offerings, conveniently accessible through an ecosystem of digital channels as well as extensive on-ground presence. The Company is listed on National Stock Exchange (NSE) and Bombay Stock Exchange (BSE) in India.

We're proud to be an equal opportunity employer. At VIL, we know that diversity makes us stronger. We are committed to a collaborative, inclusive environment that encourages authenticity and fosters a sense of belonging. We strive for everyone to feel valued, connected and empowered to reach their potential and contribute their best.

VIL's goal is to build and maintain a workforce that is diverse in experience and background but uniform in reflecting our Values of Passion, Boldness, Trust, Speed and Digital. Consequently, our recruiting efforts are directed towards attracting and retaining best and brightest talents. Our endeavour is to be First Choice for prospective employees.

VIL ensures equal employment opportunity without discrimination or harassment based on race, colour, religion, creed, age, sex, sex stereotype, gender, gender identity or expression, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy, veteran or military service status, genetic information, or any other characteristic protected by law.

VIL is an equal opportunity employer committed to diversifying its workforce.

Role Title

AGM - AGM – AI Engineer

Position No

Function

Technology – IT

Sub Function/ Vertical/ Department

Data & Analytics

Band

M2

Reports to Role (Position No)

VP – Data & Analytics

Location

Pune

Date of last update/approval

Job Purpose (In one or two sentences)

To design, build, and optimize large-scale AI solutions and data lakes by leveraging advanced Big Data frameworks (PySpark, Impala, Iceberg) to drive intelligence across enterprise operations.
To spearhead the tuning, optimization, and prompt engineering of Small Language Models (SLMs) and Large Language Models (LLMs) to deliver high-performance, cost-effective, and highly context-aware enterprise AI workflows.

Key Accountabilities / Key Result Areas (Max 5)

High-Performance AI Engineering: Build and deploy scalable AI pipelines and workflows natively utilizing PySpark, Apache Iceberg, and Impala architectures (p. 2) to process massive enterprise data streams for real-time model ingestion.
GenAI Model Optimization: Own the end-to-end evaluation, hyperparameter tuning, and fine-tuning of SLMs and LLMs to meet internal latency, accuracy, and operational cost benchmarks.
Prompt & Context Engineering: Architect advanced, robust, and secure prompt engineering frameworks, system instructions, and multi-turn agentic logic patterns to prevent hallucination and maximize reasoning capabilities.
Data Lakehouse Management: Drive optimization strategies for storage layouts within Apache Iceberg, handling schema evolution, hidden partitioning, and time-travel querying to optimize deep learning training pipelines.
Cross-Functional Governance & Industry Best Practices: Collaborate with Managed Services Partners, infrastructure leads, and external technical forums to establish stringent operational SLAs for AI application uptime, inference limits, and security protocols.

Core Competencies, Knowledge, Experience, Technical / Professional Qualifications (Max 5)

7+ Years of Experience in Domain (Telecom/IT/OEM) with 3-5 experience in handling Large Scale Telecom Network Domain
Knowledge of service performance KPIs/SLA benchmarking and strategies for continual performance improvement.
Domain Experience: 10+ Years of total experience in IT/Telecom/OEM domains, with a minimum of 5–7 years specifically handling Large-Scale Data Engineering and AI/ML model production ecosystems (p. 2).
Big Data Mastery: Strong hands-on expertise with PySpark for distributed processing, Apache Iceberg for transactional lakehouses, and Impala for high-performance interactive SQL querying on massive datasets.
Generative AI Expertise: Deep technical understanding of transformer-based architectures, model quantization techniques (GPTQ/AWQ), fine-tuning approaches (LoRA/QLoRA), and advanced context window scaling for both LLMs and resource-constrained SLMs.
Framework Fluency: Proven track record in orchestrating production-grade workflows using frameworks like LangChain, AutoGen, LlamaIndex, or CrewAI combined with custom vector databases and Graph databases .

Key Performance Indicators (Max 5)

Network Quality of Service (QoS) Adherence: Adherence to strict latency, jitter, and packet loss targets across the IP transport domain.
Capacity & Bandwidth Utilization: Optimization of link utilization percentages to prevent backhaul congestion during peak traffic hours
Model Inference Efficiency: Adherence to strict response latency, throughput, and token-cost targets across deployed enterprise GenAI apps.
Data Processing & Pipeline Latency: Percentage reduction in data-ingestion cycle times through optimized PySpark execution and Iceberg partition layouts.
Model Accuracy & Precision: Achievement of >95% accuracy/F1-scores or alignment matrix evaluation scores across customized enterprise LLM/SLM tasks.
System Availability & Scalability: Adherence to AI system uptime SLAs, parallel execution scale limits, and Mean Time to Repair (MTTR) metrics for operational pipeline failures Query Execution Performance: Optimization of Impala analytics engine utilization percentages during heavy concurrent retrieval requests

Annual Budget Owned / Key Quantitative Parameters like Workforce managed etc.

Risks, Challenges, Job Context (Short Description)

Challenges:
Managing hyper-volume, multi-structured telecommunication text, voice, and network telemetry logs under strict privacy parameters.
Navigating fast-evolving AI trends to systematically upscale infrastructure for newer concepts like Agentic AI workflows, hybrid RAG (Retrieval-Augmented Generation), and real-time streaming pipelines

Critical Risks
Model Hallucination & Data Leakage: Risks associated with poor prompt alignment, leaking proprietary enterprise data via LLM prompts, or providing wrong automated resolutions to end consumers.
Lakehouse Partition Sluggishness: Data scale outstripping query performance limitations due to suboptimal Iceberg structure layouts or inefficient Spark cluster allocations
Job purpose of Direct Reports & Dotted Reports

Direct Report / Dotted Report Position

NA

Vodafone Idea Limited (formerly Idea Cellular Limited)
An Aditya Birla Group & Vodafone partnership