We are looking for a Senior Data Software Engineer to join our team.
This role focuses on building and supporting data infrastructure that powers AI-driven products and intelligent agent systems. You'll have the opportunity to work with cutting-edge technologies and contribute to scalable, reliable platforms in a collaborative environment.
Responsibilities
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Design, build, and maintain data ingestion and processing pipelines that feed RAG systems, including handling unstructured data, images, videos, metadata, and permissions
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Administer and optimize vector database infrastructure, including Amazon Kendra with an ongoing migration to OpenSearch
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Create evaluation datasets and performance measurement frameworks for agents
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Develop monitoring and observability pipelines for AI workloads, covering latency, quality, and cost dashboards
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Implement data governance, privacy safeguards, and quality controls for AI training and inference data
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Support A/B testing and experimentation infrastructure for assessing agent iterations
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Collaborate with Backend AI engineers on data schemas and embedding strategies
Requirements
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A minimum of 3 years of data engineering experience, including direct exposure to AI/ML data infrastructure
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Strong Python skills for building data pipelines, ETL processes, and backend automation scripting
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Hands-on production experience with vector databases, including schema design and index management for Amazon Kendra or OpenSearch
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Deep understanding of search and retrieval concepts, including embedding models, chunking strategies, and retrieval optimization
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Practical knowledge of AWS services such as S3, Glue, Athena, and Kinesis (or equivalents), along with Docker and distributed data environments
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Experience embedding data quality practices such as monitoring, validation, and lineage tracking as operational defaults
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Background in designing AI/ML evaluation metrics and establishing systematic tracking through evaluation frameworks
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English language proficiency (written and spoken) at B2+ level or higher
Nice to have
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Experience with LangSmith, RAGAS, or custom evaluation framework solutions
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Background in multi-modal data processing covering unstructured text, images, and videos, along with associated governance
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Hands-on involvement with LLM fine-tuning data preparation
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Familiarity with observability tooling deeply integrated with AI calls, such as Langfuse or Arize
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Experience building streaming data pipelines using technologies such as Kafka or Kinesis
We offer
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International projects with top brands
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Work with global teams of highly skilled, diverse peers
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Healthcare benefits
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Employee financial programs
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Paid time off and sick leave
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Upskilling, reskilling and certification courses
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Unlimited access to the LinkedIn Learning library and 22,000+ courses
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Global career opportunities
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Volunteer and community involvement opportunities
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EPAM Employee Groups
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Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn
