Artificial Intelligence Engineer

Company Description

ILURA AI is a forward-thinking AI solutions company dedicated to building scalable and transformative technologies that empower businesses in a digital-first era. Our team of highly skilled engineers and data scientists specializes in areas like predictive analytics, intelligent automation, custom LLMs, and real-time decision engines. By blending innovation with precision, ILURA AI enables enterprises to achieve growth, streamline operations, and make data-backed decisions. With a commitment to excellence and security, ILURA AI is a trusted partner for organizations embracing the AI revolution.

Role Description

We are looking for a highly experienced AI Engineer to join our team on a part-time basis. You will work on designing, developing, and deploying intelligent systems and automation workflows using large language models (LLMs), vector databases, and modern cloud infrastructure.

This role is ideal for someone who has deep hands-on experience in AI development and enjoys building practical, production-level applications.

Key Responsibilities

Build and deploy AI-powered agents, chatbots, and automation systems

Develop and optimize pipelines using LangChain, LangGraph, and OpenAI APIs

Work with retrieval-augmented generation (RAG), embeddings, and vector databases

Collaborate with engineering teams to integrate AI into existing platforms

Maintain clean, scalable, and well-documented code

Requirements

3–5+ years of professional experience in AI / ML development

Strong proficiency in Python, with experience in TensorFlow or PyTorch

Hands-on experience with OpenAI APIs, embeddings, and vector stores (Pinecone, Chroma, FAISS)

Experience with FastAPI or Flask for API development

Strong understanding of LLM pipelines, prompt engineering, and orchestration tools

Self-motivated, detail-oriented, and capable of working independently

Preferred Skills

Experience with multi-agent systems or AI workflow automation

Familiarity with frontend or dashboard tools (React, Streamlit, etc.)

Exposure to data pipelines or MLOps frameworks

Compensation and Engagement

Part-time contract with competitive compensation

Fully remote with flexible hours

Opportunity for long-term or full-time collaboration based on performance