Role Objective

As an AI Engineer, you will be driving the evolution of IP-Tribe's flagship LLM Ops platform. You will develop, fine-tune, and integrate Large Language Models (LLMs) to deliver high-impact, scalable solutions for Tier-1 telecommunications and global business enterprises.

Key Responsibilities

End-to-End AI Architecture: Lead the design and implementation of complex, production-ready AI workflows, transforming LLMs into robust functional applications such as automated customer support and intelligent outage prediction.

Advanced Model Optimisation: Own the full model lifecycle, including Supervised Fine-Tuning (SFT) and advanced parameter tuning (LoRA/QLoRA) within the Tribal AI environment to optimise performance on domain-specific telco data.

Platform Extension & Engineering: Architect custom Python-based operators, data connectors, and API wrappers to expand the core capabilities and scalability of the Tribal AI platform.

Hybrid ML Solutions: Strategically apply classical machine learning and statistical modelling alongside LLMs to ensure the right tool for the right job for complex analytical tasks.

RAG & Vector Management: Design and optimise sophisticated Retrieval-Augmented Generation (RAG) pipelines, managing advanced chunking strategies, embedding selection, and vector database architecture.

Quality & Compliance Leadership: Establish performance benchmarking frameworks to evaluate model accuracy, minimise hallucinations, and ensure strict compliance with enterprise security standards.

Technical Skill Requirements

Expert Programming: Advanced Python proficiency (Pandas, NumPy, Scikit-learn, FastAPI/Flask) with an emphasis on writing clean, maintainable, and scalable production code.

ML & Deep Learning Theory: Deep understanding of machine learning theory, including supervised/unsupervised learning, feature engineering, and complex evaluation metrics.

LLM Engineering: Proven track record of integrating diverse LLMs (OpenAI, Gemini, Llama, Qwen, or DeepSeek) into enterprise-grade software.

Prompt & Reasoning Architecture: Advanced expertise in Prompt Engineering, Chain-of-Thought reasoning, and managing model parameters (Temperature, Top-P, Context Windows) for deterministic outputs.

DevOps & Infrastructure: Proficiency in Linux environments and Docker for containerised deployments, ensuring seamless CI/CD for AI models.

Preferred Skills

Proven Portfolio: A strong GitHub repository or portfolio demonstrating complex, deployed AI/ML systems (e.g., multi-agent systems, predictive telco models, or enterprise chatbots).

Advanced Tooling: Deep familiarity with Agentic workflows, MLflow, and the management of high-performance Vector Databases.

At least 1 year's experience in AI-related software development

Educational Qualifications

Bachelor's Degree in Applied Artificial Intelligence or Computer Science, or similar capacity

Completed projects using 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

Work at the cutting edge where 5G infrastructure meets Enterprise AI. In this role, you won't just use a platform; you will master and build the future of Tribal AI, delivering innovation for the world's major telecommunications players.

Artificial Intelligence Engineer