Senior AI Engineer
Role details
Job location
Tech stack
Job description
As a Senior AI Engineer at Voyfai, you will play a key role in designing, building and scaling LLM-powered and applied GenAI systems that power our core products. You will work closely with Product, Engineering and Business stakeholders to turn complex, unstructured problems into robust, production-ready AI solutions.
This role is hands-on and impact-driven. You will be expected to take end-to-end ownership, from use case discovery and prompt or model design to deployment, monitoring and continuous improvement in production, with a strong focus on real-world reliability and business impact., * Design, develop and deploy LLM-powered and GenAI features for real-world, high-impact use cases
- Build and own end-to-end GenAI pipelines, including prompt design, model selection or fine-tuning, evaluation and deployment
- Integrate foundation models into production systems with a strong focus on latency, cost, reliability and quality
- Collaborate closely with Product Managers and Engineers to translate ambiguous business problems into scalable AI solutions
- Own production AI systems, including monitoring, evaluation, guardrails and feedback loops
- Contribute to architectural decisions around AI platforms, retrieval systems, vector databases and LLMOps tooling
- Raise the technical bar through code quality, documentation and mentoring
Requirements
Do you have experience in Python?, Do you have a Master's degree?, * Several years of experience as an AI Engineer, Machine Learning Engineer or similar role, with hands-on focus on LLMs and applied GenAI in production
- Strong understanding of LLM behavior, prompting techniques, evaluation strategies and common failure modes
- Solid Python skills and experience with GenAI frameworks or tooling such as PyTorch, LangChain, LlamaIndex or similar
- Experience building production-grade GenAI systems such as RAG pipelines, agents or tool-using models
- Experience deploying and operating AI systems in cloud environments, including cost and performance optimization
- Familiarity with LLMOps or MLOps practices such as observability, testing and lifecycle management
- Pragmatic, impact-driven mindset with the ability to communicate complex AI concepts clearly
Benefits & conditions
- Competitive salary and equity options
- A dynamic, fast-paced work environment with a mission-driven team
- Flexible working arrangements (Hybrid)
- 30 days of PTO
- Regular team events and offsites
- Monthly mobility budget via Navit