The AI Innovation Engineer is a critical member of Master Works’ Innovation Department, responsible for driving the design and delivery of AI-powered PoCs and MVPs that solve real business challenges. This role requires a unique blend of engineering excellence, creativity, and applied research mindset to translate cutting-edge AI capabilities -especially those built on large language models (LLMs)-into functional and validated digital solutions. You will lead AI initiative execution across a variety of domains by leveraging pre-trained models, advanced orchestration techniques, and innovative workflows. Your primary development stack will be Python and modern AI libraries. You will also bridge innovation delivery by building lightweight APIs or frontends using Node.js and React when needed to complete a prototype or MVP.
Requirements
- Design and deliver AI-driven PoCs and MVPs that directly support strategic innovation goals across Master Works and its subsidiaries.
- Develop full-stack AI systems with Python at the core—using frameworks like FastAPI, Transformers, LangChain, Haystack, and PyTorch—to implement AI pipelines and intelligent service components.
- Integrate and orchestrate LLMs using: - Retrieval-Augmented Generation (RAG) - - - - Knowledge-Augmented Generation (KAG) Model Context Protocol (MCP) Multi-agent orchestration and A2A workflows Prompt engineering and fine-tuning where applicable
- Interface with LLM providers (OpenAI, Claude, Groq, Cohere, open-source models) through APIs and SDKs, optimizing model utility and cost-efficiency.
- Design and manage vector-based search architectures using tools like ChromaDB, Weaviate, Pinecone, or FAISS.
- Prototype interaction layers, visual interfaces, and lightweight dashboards using Node.js and React, especially for showcasing PoC/MVP deliverables.
- Collaborate with business stakeholders to shape and prioritize AI use cases, ensuring alignment with internal innovation streams and subsidiary needs.
- Evaluate, benchmark, and refine AI models for accuracy, performance, and business relevance.
- Create internal documentation, reusable components, and technical guidelines to support scaling and knowledge sharing.
- Stay up to date with emerging AI trends and continuously integrate relevant new methods into practice.
Required Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Engineering, or a related technical field.
- 5+ years of hands-on experience delivering AI-based systems with tangible outcomes.
- Demonstrated mastery of Python for building AI workflows, services, and integrations using leading AI/ML frameworks. Proven experience in developing and integrating LLM-based applications using APIs, SDKs, and orchestration tools.
- Solid knowledge of RAG, embeddings, vector databases, and prompt tuning techniques.
- Familiarity with autonomous agent design patterns (e.g., A2A, task chaining, multi-agent flow control).
- Working knowledge of Node.js and React for full-stack PoC/MVP assembly.
- Strong experience with cloud-native development, containerization (e.g., Docker), and modern development practices.
Preferred Qualifications
- Experience building Arabic-aware NLP solutions or localized AI models (e.g., Najdi dialect adaptation, intent classification in Arabic).
- Background in deploying AI innovations in government, defense, or regulated sectors. Experience working in high-velocity innovation teams or R&D-style workstreams.
- Familiarity with tools like MLflow, LangSmith, or Weights & Biases for experiment tracking.
- Contributions to AI open-source initiatives, technical publications, or public demos is a plus.
Core Competencies:
- Innovation-first mindset with ability to rapidly turn ideas into working prototypes.
- Strong ownership, able to independently manage priorities and delivery.
- Analytical thinker with the ability to simplify complex technical ideas.
- Results-driven with a focus on experimentation and measurable outcomes.
- Excellent communication skills, capable of articulating technical ideas to diverse stakeholders.
- Ability to work in multi-disciplinary teams and dynamic business environments.
- Passion for AI and continuous learning of emerging tools, models, and practices.
