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Senior Data Engineer, AI
EPAM SystemsUnited States🇺🇸United StatesPosted 8 Jul 2026
Quick Overview
Work Type
Hybrid
Level
Mid Senior
Job Description
We are looking for a Senior Data Engineer with AI to architect and build intelligent AI workflows that merge models, enterprise data, and business logic into dependable, production-ready solutions. Within this position, you will construct scalable AI deployment pipelines, embed AI functionality into enterprise systems, and partner with data scientists and business experts to deliver secure, transparent, and compliant AI behavior. Responsibilities Architect and build AI workflows that merge models, prompts, enterprise data, tools, and business logic Create and sustain prompt engineering approaches, covering versioning, testing, and optimization Deploy orchestration layers supporting multi-step reasoning, decisioning, and action execution Embed AI functionality within enterprise systems, APIs, and user interfaces Apply guardrails that guarantee secure, transparent, and compliant AI behavior Construct and sustain production-grade AI deployment pipelines Guarantee dependability, scalability, latency optimization, and cost efficiency of AI services Deploy monitoring and observability for AI systems covering usage, performance, drift, and failures Set up change control, versioning, rollback, and release management practices Work closely alongside data scientists and business experts to verify model behavior and outputs Convert experimentation outcomes into dependable production-ready solutions Convey operational constraints and engineering considerations to stakeholders Requirements More than 3 years of experience working in software development Solid engineering foundation paired with applied AI expertise Proficiency in architecting and building AI workflows that merge models, prompts, and enterprise data Mastery of prompt engineering approaches, covering versioning, testing, and optimization Abilities in constructing production-grade AI deployment pipelines, MLOps, and productionization Proficiency in monitoring and observability for AI systems, covering drift, performance, and failures Understanding of change control, versioning, and release management practices Ability to rapidly get up to speed on new platforms and tools Experience with large-scale enterprise data ecosystems English skills at B2 level or above
Skills
MLOps
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