Senior NLP & Generative AI Engineer

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As a Senior NLP & Generative AI Engineer, you will lead the development of the AI intelligence backbone of our platform, with a strong focus on Deep Search, Retrieval-Augmented Generation (RAG), Embedding Models, and Agentic AI workflows tailored for IP domain use cases.


Responsibilities:

  • Build advanced Deep Search systems that extract, synthesise, and correlate information from large-scale patent, legal, scientific, and technical corpora
  • Architect AI-driven frameworks to generate high-fidelity Deep Search Reports, including insights, novelty mapping, contextual relevance, comparative analysis, and traceable references.
  • Ensure domain accuracy, factual integrity, and compliance with IP standards.
  • Design, develop, and optimise RAG pipelines for IP and research-intensive content to ensure precision and context-aligned generation.
  • Implement robust grounding, context-injection, and validation mechanisms to reduce hallucinations.
  • Define evaluation frameworks and continuous improvement loops for retrieval quality and response depth.
  • Fine-tune LLMs using LoRA, PEFT, SFT, and domain adaptation to enhance reasoning for legal-technical content.
  • Build and optimise domain-specific embedding models for the semantic understanding of patents and research literature.
  • Design efficient chunking, context-handling, and long-document processing strategies.
  • Develop agent-based AI workflows that support multi-step reasoning, structured research, validation, and automated analysis tasks.
  • Combine retrieval, reasoning, domain knowledge, and tool execution to achieve reliable and auditable outcomes.
  • Apply advanced NLP techniques for summarisation, information extraction, knowledge representation, and structured transformation.
  • Implement quality, safety, explainability, and audit mechanisms required for enterprise and legal-grade AI usage.


Requirements:

  • Deep knowledge of NLP, Generative AI, RAG, and Deep Search systems
  • Proven experience building AI systems for knowledge-intensive or specialised text domains
  • Hands-on expertise with: Python, PyTorch, Hugging Face Transformers, Vector search systems such as FAISS, Pinecone, Weaviate, or Chroma, LLM orchestration frameworks (LangChain, LlamaIndex).
  • Strong analytical mindset with the ability to convert research into production-grade systems.
  • Excellent written communication and documentation abilities.


Behavioural and Work Attributes:

  • High ownership, product-oriented thinking, and commitment to quality in a fast-paced environment.
  • Ability to collaborate with cross-functional teams, including engineering, product, domain specialists, and leadership.
  • Curiosity, innovation mindset, and passion for solving deep-tech AI problems.


Nice to Have:

  • Experience in IP, LegalTech, research-intensive domains, scientific publishing, or knowledge-based platforms.
  • Exposure to MLOps for AI model deployment, monitoring, evaluation, and lifecycle management.
  • Familiarity with agent frameworks (LangGraph, AutoGen, CrewAI).
  • Background in deep-tech, AI-first product companies or R& D-driven teams.
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