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GenAI / LLM Engineer – Domain-Specific AI Solutions (Telecom)

GenAI / LLM Engineer – Domain-Specific AI Solutions (Telecom)

MobileumDelhi, India
20 hours ago
Job description

About Us :

Mobileum is a leading provider of Telecom analytics solutions for roaming, core network, security, risk management, domestic and international connectivity testing, and customer intelligence. More than 1,000 customers rely on its Active Intelligence platform, which provides advanced analytics solutions, allowing customers to connect deep network and operational intelligence with real-time actions that increase revenue, improve customer experience, and reduce costs. Know our story :

in Silicon Valley, Mobileum has global offices in Australia, Dubai, Germany, Greece, India, Portugal, Singapore and UK with global HC of 1800+.

Join Mobileum Team

At Mobileum we recognize that our team is the main reason for our success. What does work with us mean? Opportunities!

Role Overview :

We are seeking a highly skilled

GenAI / LLM Engineer

to design, fine-tune, and operationalize

Large Language Models (LLMs)

for telecom business applications. This role will be instrumental in building

domain-specific GenAI solutions , including the development of

domain-specific LLMs , to transform telecom operational processes, customer interactions, and internal decision-making workflows.

Key Responsibilities :

Build domain-specific LLMs

by curating domain-relevant datasets and training / fine-tuning LLMs tailored for telecom use cases.

Fine-tune

pre-trained LLMs

(e.g., GPT, Llama, Mistral) using

telecom-specific datasets

to improve task accuracy and relevance.

Design and implement

prompt engineering frameworks , optimize prompt construction and context strategies for telco-specific queries and processes.

Develop

Retrieval-Augmented Generation (RAG)

pipelines integrated with vector databases (e.g., FAISS, Pinecone) to enhance LLM performance on internal knowledge.

Build

multi-agent LLM pipelines

using orchestration tools (LangChain, LlamaIndex) to support complex telecom workflows.

Collaborate cross-functionally with

data engineers ,

product teams , and

domain experts

to translate telecom business logic into GenAI workflows.

Conduct systematic

model evaluation

focused on minimizing hallucinations, improving domain-specific accuracy, and tracking performance improvements on business KPIs.

Contribute to the development of

internal reusable GenAI modules , coding standards, and best practices documentation.

Required Skills :

Advanced knowledge of

transformer architectures , fine-tuning techniques (LoRA, PEFT, adapters), and

transfer learning .

Proficiency in

Python , with significant experience using

PyTorch ,

Hugging Face Transformers , and related NLP libraries.

Practical expertise in

prompt engineering ,

RAG pipelines , and

LLM orchestration tools

(LangChain, LlamaIndex).

Ability to build

domain-adapted LLMs , from data preparation to final model deployment.

Desirable Bonus Skills :

Familiarity with

multi-modal LLMs

(text + tabular / time-series).

Experience with

OpenAI function calling ,

LangGraph , or

agent-based orchestration .

Exposure to

telecom datasets

(e.g., call records, customer tickets, network logs).

Experience with

low-latency inference optimization

(e.g., quantization, distillation).

Experience : 6–8 years

of professional experience in

AI / ML , with at least

2+ years

of practical exposure to

LLMs

or

GenAI deployments .

Hands-on experience in

fine-tuning transformer models , prompt engineering, and

RAG architecture design .

Experience delivering

production-ready AI solutions

in enterprise environments; telecom exposure is a plus.

Qualifications : Master’s or Ph.D. in

Computer Science ,

Artificial Intelligence ,

Machine Learning ,

Natural Language Processing , or a related field.

Ph.D. preferred

for foundational model work and advanced research focus.

What We Offer : Opportunity to lead

cutting-edge GenAI initiatives

in the telecom sector.

High ownership of end-to-end productization lifecycle of

domain-specific LLMs .

Collaborative environment with

AI, telecom, and product leaders .

Competitive compensation with options for

rapid career growth

in an enterprise AI transformation journey.

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