We are looking for a passionate and highly motivated Graduate Engineer Trainee – AI/LLM Engineer (Telecom AI Ops) to join Mavenir's MavAI OPS (Agentic Service Assurance Platform) team. In this role, you will contribute to the development of next-generation AI-powered operational systems that help telecom operators monitor, analyze, troubleshoot, and autonomously manage network operations.

You will work with cutting-edge technologies including Large Language Models (LLMs), Agentic AI, Retrieval Augmented Generation (RAG), Generative AI, Python development, AI-driven Root Cause Analysis, and Cloud-Native Telecom Platforms. Working alongside experienced engineers and AI specialists, you will develop intelligent solutions that analyze alarms, correlate events, investigate incidents, generate recommendations, and continuously improve operational efficiency through AI.

This opportunity is ideal for fresh graduates who are passionate about Artificial Intelligence, Machine Learning, Generative AI, Python development, and cloud-native technologies, and who are eager to build innovative AI solutions for the telecom industry.

Key Responsibilities

AI & LLM Engineering

• Develop AI-powered applications using Large Language Models such as GPT, Llama, Claude, and Azure OpenAI.
• Design, build, and optimize Retrieval Augmented Generation (RAG) pipelines.
• Create prompts, workflows, and agent orchestration frameworks for AI systems.
• Develop multi-agent AI systems for automated incident investigation and troubleshooting.
• Support fine-tuning, testing, evaluation, and optimization of AI models for telecom operational use cases.
• Integrate LLM applications with enterprise knowledge bases, operational tools, and business systems.

Python Development & Automation

• Develop Python-based applications, microservices, and REST APIs.
• Build automation workflows to improve operational efficiency and reduce manual effort.
• Develop data ingestion, transformation, and AI processing pipelines.
• Create tools for telemetry, alarm, log, and KPI analysis.
• Implement integrations with OSS, monitoring, and ticketing systems.

AI Operations & Analytics

• Analyze network alarms, logs, and performance metrics using AI and machine learning techniques.
• Support the development of AI-driven root cause analysis and recommendation engines.
• Design knowledge retrieval frameworks using embeddings and vector databases.
• Improve AI assistant accuracy through continuous evaluation, testing, and feedback loops.
• Contribute to operational intelligence and autonomous network management capabilities.

Cloud & Platform Engineering

• Work with containerized and cloud-native environments such as Kubernetes and OpenShift.
• Deploy, monitor, and maintain AI applications in distributed environments.
• Support observability, monitoring, and performance optimization initiatives.
• Collaborate with engineering teams to ensure scalability, reliability, and maintainability of AI solutions.

Job Requirements

Education

• B.E./B.Tech/M.Tech in:
• Computer Science
• Artificial Intelligence
• Data Science
• Information Technology
• Electronics & Communication Engineering
• Telecommunications
• Fresh Graduates (2025/2026 Pass-outs)

Core Technical Skills

Programming (Strongly Preferred)

• Python (Mandatory)
• Object-Oriented Programming (OOP)
• REST APIs
• FastAPI and/or Flask

AI & Machine Learning

• Understanding of Large Language Models (LLMs)
• Generative AI concepts and applications
• Prompt Engineering
• Retrieval Augmented Generation (RAG)
• Embeddings and Semantic Search
• Vector Databases
• AI Evaluation Techniques
• Machine Learning Fundamentals

AI Frameworks & Platforms

Exposure to one or more of:

• LangChain
• LangGraph
• LlamaIndex
• Semantic Kernel
• Azure OpenAI
• Hugging Face
• OpenAI APIs

Requirements

• Strong programming and problem-solving skills.
• Good understanding of AI, machine learning, and Generative AI concepts.
• Ability to learn quickly and work in a fast-paced R&D environment.
• Strong analytical and troubleshooting capabilities.
• Effective verbal and written communication skills.
• Ability to collaborate within cross-functional engineering teams.
• Passion for innovation and emerging AI technologies.

Nice to Have

Cloud-Native Technologies

• Kubernetes
• Docker
• OpenShift

Databases & Data Technologies

• SQL
• MongoDB
• ElasticSearch
• Neo4j
• Vector Databases

Domain Knowledge

• Exposure to Telecom OSS/BSS environments.
• Understanding of network operations, alarms, KPIs, and service assurance concepts.
• Experience with AI-powered analytics or automation projects.
• Academic, internship, or personal projects involving LLMs, RAG, agents, or Generative AI applications.