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Role Summary 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 ScienceArtificial IntelligenceData ScienceInformation TechnologyElectronics & Communication EngineeringTelecommunicationsFresh Graduates (2025/2026 Pass-outs) Core Technical Skills Programming (Strongly Preferred) Python (Mandatory)Object-Oriented Programming (OOP)REST APIsFastAPI and/or FlaskAI & Machine Learning Understanding of Large Language Models (LLMs)Generative AI concepts and applicationsPrompt EngineeringRetrieval Augmented Generation (RAG)Embeddings and Semantic SearchVector DatabasesAI Evaluation TechniquesMachine Learning FundamentalsAI Frameworks & Platforms Exposure to one or more of: LangChainLangGraphLlamaIndexSemantic KernelAzure OpenAIHugging FaceOpenAI 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 KubernetesDockerOpenShiftDatabases & Data Technologies SQLMongoDBElasticSearchNeo4jVector 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. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.