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EPAM
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Lead AI Engineer

EPAMIndia, Hyderabad; India, Bangalore; India, Pune; India, Gurgaon
Work model
Office
Experience
1+ years
Employment
Not specified
Compensation
Not disclosed
Technology signal
31 tags

Technology context

31

Parsed from the vacancy text; ordered by relevance to this role.

AILLMAWSGenAIMachine LearningAzurePythonRAGGCPKubernetesPyTorchTensorFlowCloudDockerMicroservicesAPIDatabricksCI/CDAirflowAI Native EngineeringAutoGen FrameworkAWS BedrockAzure Machine LearningAzure OpenAI ServiceChromaCrewAIGoogle Vertex AIHugging Face TransformersLangChainMicroservice Architecture StyleQdrant

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Role description

We are seeking a Lead AI Engineer to pioneer innovative AI and machine learning solutions, shaping the development and deployment of cutting-edge generative AI applications. This role offers the opportunity to lead the charge in creating AI-driven efficiencies and impactful business outcomes while collaborating with diverse teams across the organization.

Responsibilities

  • Build and deploy scalable AI/ML models and GenAI solutions in production
  • Design and maintain robust ETL pipelines and data workflows
  • Develop LLM-based applications using modern frameworks
  • Implement prompt engineering techniques for optimized AI outputs
  • Deploy models via APIs and integrate with enterprise applications
  • Ensure end-to-end ownership, including development, deployment, monitoring, and optimization
  • Collaborate with cross-functional teams to deliver business-driven AI solutions

Requirements

  • 8-13 years of general IT experience
  • 8+ years of experience in AI Engineering
  • At least 1 year of relevant leadership experience
  • Strong programming skills in Python
  • Hands-on experience with ETL and Data Pipelines
  • Expertise in ML/DL frameworks such as TensorFlow, PyTorch, Scikit-learn
  • Understanding of Prompt Engineering and working with LLMs
  • Familiarity with LLM frameworks like LangChain, LlamaIndex, Hugging Face
  • Cloud experience with Azure, AWS, or GCP
  • Proficiency in MLOps tools like MLflow, Kubeflow, Airflow
  • Strong experience in API development and Model Deployment
  • B2 level of English or higher, with an emphasis on technical communication skills

Nice to have

  • Experience with RAG architectures and vector databases
  • Knowledge of real-time or streaming data pipelines
  • Exposure to scalable system design and microservices architecture
  • Showcase of expertise in Databricks, PySpark
  • Background in Cloud Data Solutions and ETL Pipelines