Generative AI Lead Engineer

As a GenAI LeadEngineer, you will lead our engineering initiatives to drive transformative advancements across multiple industries—including Agentic AI, Generative AI Copilots, Retrieval-Augmented Generation (RAG) technologies, virtual assistants, and advanced language processing applications. You'll be responsible for leading technical initiatives, mentoring team members, and driving innovation in applications that require sophisticated language understanding and realistic outputs. We're looking for a passionate, experienced GenAI LeadEngineer to guide our talented AI engineering team, empowering them to deliver robust, scalable, and impactful AI solutions for our customers. Some key responsibilities: Leading the design, implementation, and enhancement of NLP and generative AI models, using frameworks and tools such as GPT, LLaMA, LangGraph, Langfuse, Hugging Face, etc. Defining and developing proprietary integrations with existing third-party solutions (e.g., Microsoft Copilot, OpenAI APIs) to provide best-in-class generative AI capabilities tailored specifically to our customers' needs. Collaborating strategically with cross-functional teams—including Head of AI, AI Engineers, Full-Stack Developers, and Product Managers—to define clear AI project requirements, objectives, and ensure alignment with business goals. Conducting proactive research to stay at the forefront of NLP and generative AI advancements, continuously identifying opportunities to integrate cutting-edge techniques into Faktion’s offerings. Optimizing and scaling NLP and generative AI models to achieve superior performance, efficiency, and operational reliability. Overseeing the development and maintenance of robust MLOps pipelines, encompassing data preprocessing, model training, fine-tuning, evaluation, deployment, and monitoring. Building and managing containerized AI back-end services using technologies such as Docker and FastAPI. Creating and maintaining high-quality documentation—including technical specifications, user manuals, and presentations—to effectively communicate complex AI solutions to technical and business stakeholders. Establishing, enforcing, and continuously evolving best practices, standards, and procedures within the NLP and generative AI engineering team. Providing technical mentorship, guidance, and leadership to engineers and junior team members, fostering professional growth and technical excellence. Advanced degree (Master's or Ph.D.) in Computer Science, Natural Language Processing, Artificial Intelligence, Machine Learning, or a related field. 5+ years of experience with implementing NLP and generative AI models, with deep expertise in transformer architectures, language models, and embeddings. Demonstrated leadership experience in technical AI/ML projects, including team mentoring and project management. Expert-level proficiency in Python and extensive experience with machine learning libraries (PyTorch, TensorFlow, Hugging Face transformers). Strong understanding of natural language processing techniques, including text classification, named entity recognition, sentiment analysis, and language generation. Proven experience with large language model fine-tuning, prompt engineering, and evaluation methodologies. Solid knowledge of data structures, algorithms, and software engineering principles. Experience with cloud-based platforms and services such as Azure, with a focus on scalable AI solutions. Familiarity with software development methodologies such as Agile or Scrum. Exceptional problem-solving skills with the ability to think critically and creatively to develop innovative AI solutions. Strong communication and presentation skills with the ability to effectively convey complex technical concepts to diverse audiences. Proactive mindset with the ability to work independently and lead teams in a fast-paced, dynamic environment. The following experiences are a plus: Open-source contributions to Generative AI or NLP projects Active GitHub repositories demonstrating advanced NLP implementations or prior engagements in relevant Kaggle competitions Proven track record of designing and deploying scalable language models in production environments Publications in relevant NLP/AI/ML conferences and journals (ACL, EMNLP, NeurIPS, ICML, etc.) Experience in one of our focus domains: Data Quality, Retail, Manufacturing, Finance Knowledge of multilingual NLP and cross-lingual transfer learning We offer: A rewarding salary package that includes additional perks like a company car and fuel card or a mobility budget, comprehensive hospitalization, group insurance, and a top-tier laptop and smartphone A company culture that stimulates both individual and team development, fostering professional growth and leadership opportunities Regular team-building activities and gatherings, providing great opportunities to unwind and engage with our vibrant team initiatives A flexible hybrid working policy to choose where, how, and when you want to work Opportunities to represent Faktion at industry conferences and events #J-18808-Ljbffr