Lead AI Engineer

EPAM Systems


Date: 18 hours ago
City: Remote, Remote
Contract type: Full time
Remote
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

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