About This Role
This role sits at the intersection of Generative AI engineering and enterprise product development. You will serve as a GenAI subject matter expert and hands-on architect, building production-ready solutions that combine LLMs, vector databases, and API integrations with a focus on privacy, security, and business outcomes.
What You Will Do
- Build scalable software solutions using LLMs and other ML models to solve complex enterprise challenges
- Architect and develop enterprise-grade AI solutions with focus on privacy, security, fairness, and responsible AI practices
- Design AI output structures (JSON, HTML, nested nodes) that can be consumed directly by downstream dashboards with minimal development overhead
- Build extensible API integrations and low-code UI/UX solutions to extract, process, and surface AI insights in high-performing dashboards
- Work with Product Development as a GenAI subject matter expert, envision solution outcomes and design viable architectures to meet them
- Understand how AI models interpret datasets and build prompts that reliably produce expected outcomes
- Architect and develop infrastructure for scalable, distributed ML systems
- Work with frameworks including TensorFlow, PyTorch, Hugging Face, LangChain, and LlamaIndex
- Optimise generative AI models for performance, scalability, and efficiency
- Develop and maintain AI pipelines, data preprocessing, feature extraction, model training, evaluation, and deployment
- Contribute to the establishment of best practices and standards for GenAI development
What You Need to Succeed
- 6+ years overall experience; 5+ years full-stack engineering (C#, Python)
- Proficiency in designing architecture, building API integrations, configuring cloud services, and setting up authentication, monitoring, and logging
- Production experience implementing AI systems, computer vision, NLP, and/or enterprise AI at scale
- Experience with vector databases (Pinecone or equivalent) for information retrieval
- Strong understanding of NLG and GenAI, transformers, LLMs, text embeddings
- Experience designing scalable classification, text extraction, and data connector systems across formats (PDF, CSV, DOCX)
- ML libraries and frameworks: PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex
- 3+ years in a technical leadership role setting technical direction for project teams
- Programming proficiency in C/C++, Java, and Python
- Excellent problem-solving and communication skills for both technical and non-technical audiences
What Will Give You an Edge
- Experience with cloud-based platforms, AWS, GCP, or Azure
- Exposure to self-supervised learning, transfer learning, and reinforcement learning
What Qfyre Offers
- GenAI leadership role with genuine technical ownership and cross-functional influence
- Exposure to cutting-edge LLM and RAG architectures at enterprise scale
- Competitive compensation package with remote-first flexibility
- Opportunity to define GenAI best practices for a high-growth enterprise programme
Skills and Technologies
Apply for Machine Learning Lead Analyst, Generative AI
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