Lead AI Engineer

We're looking for a seasoned Lead AI Engineer to spearhead innovative AI and machine learning initiatives, guiding the development and rollout of state-of-the-art generative AI applications. This position gives you the chance to take charge of driving AI-powered efficiencies and meaningful business results while working alongside varied teams throughout the organization.

Responsibilities

• Construct and launch scalable AI/ML models and GenAI-based solutions into live production environments
• Build and sustain dependable ETL pipelines and data workflow processes
• Create applications powered by LLMs using contemporary development frameworks
• Apply prompt engineering strategies to maximize the quality of AI-generated outputs
• Roll out models through APIs and connect them with enterprise-level applications
• Take complete ownership across the lifecycle, covering development, deployment, tracking, and refinement
• Team up with cross-functional groups to produce AI solutions aligned with business goals
  
  

Requirements

• Between 8 and 13 years of broad IT experience
• More than 8 years specifically focused on AI Engineering
• At least 1 year of relevant experience in a leadership role
• Solid programming ability in Python
• Direct experience building ETL processes and data pipelines
• Strong background in ML/DL frameworks, such as TensorFlow, PyTorch, and Scikit-learn
• Working knowledge of prompt engineering practices and hands-on LLM experience
• Familiarity with LLM-focused frameworks like LangChain, LlamaIndex, and Hugging Face
• Practical experience with cloud platforms such as Azure, AWS, or GCP
• Capability using MLOps tooling, including MLflow, Kubeflow, and Airflow
• Solid background in API development and deploying models into production
• English proficiency at a B2 level or higher, with particular strength in technical communication
  
  

Nice to have

• Background working with RAG architectures and vector database technology
• Familiarity with real-time or streaming data pipeline design
• Exposure to designing scalable systems and microservices-based architecture
• Demonstrated skill with Databricks and PySpark
• Experience with cloud-based data solutions and ETL pipeline development