- Location
- Antwerp, Vlaams Gewest, Belgium
- Workplace
- Hybrid
- Type
- Full-time
- Department
- Machine Learning
- Seniority
- Mid
- Experience
- 5+ years
- Education
- PhD
- Source
- Recruitee
Description
As a GenAI Lead Engineer, you will lead our engineering initiatives to drive transformative advancements across multiple industries, including Multi-Agent AI / Generative AI Applications, Retrieval-Augmented Generation (RAG) technologies, voice AI 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. You will oversee our proprietary 'Evaluation-Driven Development' processes across all AI Projects
We're looking for a passionate, experienced GenAI Lead Engineer 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/agentic AI models, using various SOTA frameworks and tools
Defining and developing proprietary integrations with existing third-party solutions to provide best-in-class generative AI capabilities tailored specifically to our customers' needs.
Collaborating strategically with cross-functional teams, including the Head of AI, AI Engineers, Full-Stack Developers, and Product Managers, to define clear AI project requirements and objectives, and ensure alignment with business goals.
Conducting proactive research to stay at the forefront of NLP and generative/agentic AI advancements, continuously identifying opportunities to integrate cutting-edge techniques into Faktion’s offerings.
Optimising and scaling NLP and generative AI systems 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 containerised 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.