We’re looking for a
**Lead AI Engineer,**
with a strong data science foundation, to design, build, and scale production-grade AI systems across LLMs, RAG, and agent-based architectures. This is a hands-on leadership role at the intersection of AI Engineering, Data Science, and modern LLMOps, focused on delivering AI solutions that are not just innovative, but reliable, measurable, and trusted in production.
As part of this role, you will also shape how AI systems are evaluated and monitored, ensuring
**consistent performance, grounded and reliable outputs and clear visibility into system behavior.**
**What You’ll Do:**
- Lead the AI evaluation discipline within the engineering organization;
- Design and implement evaluation methodologies for LLM and AI systems;
- Design statistical evaluation methods for AI model performance;
- Collaborate on data pipelines, feature engineering, and context design;
- Contribute to LLMOps / MLOps practices (CI/CD, monitoring, lifecycle management);
- Build and deploy LLM, RAG, and agent-based solutions;
- Integrate AI systems into existing platforms and data ecosystems;
- Lead technical discussions and mentor team members.
**Who are you:**
- 5+ years in AI Engineering, Machine Learning, or Data Science;
- Strong experience with Python and modern AI frameworks;
- Hands-on experience with LLMs, RAG, or agent-based systems;
- Understanding of cloud platforms (Azure, AWS, or GCP);
- Experience building production-grade systems;
- Strong problem-solving and communication skills.
**Nice to Have:**
- Experience with AI evaluation frameworks or benchmarking approaches;
- Familiarity with observability tools (e.g. Langfuse, tracing, monitoring);
- Experience with MLflow or experiment tracking tools;
- Knowledge of vector databases, semantic search, or knowledge graphs;
- Experience with Azure OpenAI or similar platforms;
- Background in statistics or experimentation design;
- Experience mentoring or leading engineers.
We appreciate the interest of all applicants. Please note that only those whose qualifications align closely with the position requirements will be contacted for the next steps in the selection process.
All applications will be handled with confidentiality.
IW\_Privacy Protection Statement for Job Applicants
**Lead AI Engineer,**
with a strong data science foundation, to design, build, and scale production-grade AI systems across LLMs, RAG, and agent-based architectures. This is a hands-on leadership role at the intersection of AI Engineering, Data Science, and modern LLMOps, focused on delivering AI solutions that are not just innovative, but reliable, measurable, and trusted in production.
As part of this role, you will also shape how AI systems are evaluated and monitored, ensuring
**consistent performance, grounded and reliable outputs and clear visibility into system behavior.**
**What You’ll Do:**
- Lead the AI evaluation discipline within the engineering organization;
- Design and implement evaluation methodologies for LLM and AI systems;
- Design statistical evaluation methods for AI model performance;
- Collaborate on data pipelines, feature engineering, and context design;
- Contribute to LLMOps / MLOps practices (CI/CD, monitoring, lifecycle management);
- Build and deploy LLM, RAG, and agent-based solutions;
- Integrate AI systems into existing platforms and data ecosystems;
- Lead technical discussions and mentor team members.
**Who are you:**
- 5+ years in AI Engineering, Machine Learning, or Data Science;
- Strong experience with Python and modern AI frameworks;
- Hands-on experience with LLMs, RAG, or agent-based systems;
- Understanding of cloud platforms (Azure, AWS, or GCP);
- Experience building production-grade systems;
- Strong problem-solving and communication skills.
**Nice to Have:**
- Experience with AI evaluation frameworks or benchmarking approaches;
- Familiarity with observability tools (e.g. Langfuse, tracing, monitoring);
- Experience with MLflow or experiment tracking tools;
- Knowledge of vector databases, semantic search, or knowledge graphs;
- Experience with Azure OpenAI or similar platforms;
- Background in statistics or experimentation design;
- Experience mentoring or leading engineers.
We appreciate the interest of all applicants. Please note that only those whose qualifications align closely with the position requirements will be contacted for the next steps in the selection process.
All applications will be handled with confidentiality.
IW\_Privacy Protection Statement for Job Applicants
