Artificial Intelligence Engineer

As an AI Engineer, you will be the technical engine behind Tribal AI, IP-Tribe's flagship LLMOps platform. You will develop, tune, and integrate Large Language Models (LLMs) to create high-impact demos, MVPs, and solutions for Tier-1 telecommunications and business enterprises.

Key Responsibilities

AI Use-Case Integration: Design and implement end-to-end AI workflows by integrating LLMs into functional business applications (e.g., automated customer support, network log analysis, or intelligent outage prediction).

Model Fine-Tuning & Optimisation: Perform supervised fine-tuning (SFT) and parameter tuning (hyperparameters, LoRA/QLoRA) within the Tribal AI environment to adapt base models to domain-specific telco data. (Good to have but not compulsory)

Rapid MVP Development: Use Python to build custom operators, data connectors, and API wrappers that extend the Tribal AI platform's core capabilities.

ML Modelling: Apply classical machine learning and statistical modelling techniques where LLMs alone aren't enough, ensuring the right tool for the right job.

RAG Architecture: Build and optimise Retrieval-Augmented Generation (RAG) pipelines, focusing on chunking strategies, embedding selection, and vector database management.

Performance Benchmarking: Evaluate model outputs using testing tools to ensure accuracy, reduced hallucination, and compliance with enterprise security standards.

Technical Skill Requirements

Core Programming: Advanced Python coding skills (Pandas, NumPy, Scikit-learn, Fast API/Flask).

ML Fundamentals: A solid working knowledge of machine learning theory, including supervised/unsupervised learning, model evaluation metrics, and feature engineering.

LLM Proficiency: * Experience integrating LLMs (OpenAI, Gemini, Llama, Qwen, or DeepSeek) into software applications.

Understanding of Model Parameters (Temperature, Top-P, Context Windows) and their impact on output.

Practical project experience in Prompt Engineering and Chain-of-Thought reasoning.

Infrastructure: Comfortable working in Linux environments and using Docker for containerised deployments.

Project Portfolio: Demonstrated experience through a GitHub repository or portfolio showcasing completed ML/AI projects (e.g., chatbots, sentiment analysers, or predictive models).

Tooling: Familiarity with Tools that enable AI/Agentic workflow, ML flow or Vector DBs

Educational Qualifications

Bachelor's Degree in Computer Science, Data Science, or a related field with a strong emphasis on AI/ML.

Completed projects using an AI tech stack

Good understanding of Object-Oriented Programming

Full-stack development and good understanding of SDLC

Experienced working in a project team

Why Join IP-Tribe

You will work at the intersection of 5G infrastructure and Enterprise AI. This role offers the unique opportunity to master the industry-leading LLM Ops platform, while building the future of Tribal AI for major telecommunications players and enterprise markets.