Middle GenAI Engineer

At LeverX, we have had the privilege of delivering over 1,500 projects. With 20+ years in the market, our team of 2,200+ is strong, reliable, and always evolving: learning, growing, and striving for excellence.

We are looking for a Middle GenAI Engineer to join us. Learn more about our team from this interview. 

what we offer:

• Projects in different domains: Healthcare, manufacturing, e-commerce, fintech, etc.
• Projects for every taste: Startup products, enterprise solutions, research & development projects, and projects at the crossroads of SAP and the latest web technologies.
• Global clients based in Europe and the US, including Fortune 500 companies.
• Employment security: We hire for our team, not just a specific project. If your project ends, we will find you a new one.
• Healthy work atmosphere: On average, our employees stay in the company for 4+ years.
• Market-based compensation and regular performance reviews.
• Internal expert communities and courses.
• Perks to support your growth and well-being.

required skills:

• 2+ years of experience as a backend developer, including building FastAPI and Django microservices and working with REST/gRPC APIs.
• Hands-on experience with GenAI tools and frameworks, including LangChain, LlamaIndex, and RAG pipelines.
• Knowledge of AI integration patterns: prompt engineering, model fine-tuning, and vector database optimization.
• English B2+.

responsibilities:

• Design and deploy microservices and backend systems with a focus on generative AI and chatbot applications.
• Integrate and optimize third-party AI products, including LLMs and related orchestration frameworks.
• Optimize AI pipelines using vector databases such as Pinecone, Chroma, and Vanna and tools like LangChain and LlamaIndex to efficiently generate retrieval-augmented data.
• Collaborate with cross-functional teams to capture, clarify, and translate stakeholder requirements into technical solutions.
• Stay ahead of AI trends by prototyping emerging tools and standards: OpenAI APIs, AI agents, multimodality.
• Ensure adherence to AI protocols, standards, and best practices throughout the software development lifecycle.