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Senior AI Agent Developer with AWS, Databricks

EPAM SystemsUnited States🇺🇸United StatesPosted 31 Jul 2026

Why This Role Stands Out

This hybrid role offers you the chance to build and deploy cutting-edge AI solutions at scale, leveraging your expertise in AWS and Databricks within a collaborative and innovative team environment. You'll thrive here if you possess strong end-to-end ML/AI experience and a passion for MLOps, making a significant impact on production-ready AI initiatives. Apply now to grow your skills and contribute to exciting projects with EPAM Systems.

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
3 weeks ago
AWSMLOpsDatabricks

Job Description

We are looking for a hands-on Senior AI Agent Developer to build, deploy, and maintain ML/AI solutions in production, bringing strong end-to-end experience from model development through deployment, monitoring, and scaling.

Responsibilities Design, build, and optimize ML/AI models and pipelines Deploy models to production, ensuring scalability, reliability, and performance Build and maintain MLOps workflows, including CI/CD, model monitoring, and retraining Work with large-scale data to engineer features and prepare training datasets Collaborate with data engineers, product, and business teams to deliver solutions Communicate effectively with stakeholders, sharing progress, insights, and outcomes clearly Contribute to a collaborative and supportive team culture as a strong team player Troubleshoot and continuously improve models running in production Follow best practices for code quality, documentation, and responsible AI Requirements 3+ years of experience building and deploying ML/AI solutions in production environments Expertise in AWS and Databricks for building and scaling ML/AI pipelines Proficiency in MLOps practices, including CI/CD, model monitoring, and retraining workflows Skills in feature engineering and preparing training datasets from large-scale data Background in collaborating with cross-functional teams, including data engineers, product, and business stakeholders Competency in clear stakeholder communication, sharing progress, insights, and outcomes Understanding of best practices for code quality, documentation, and responsible AI English proficiency at B2 level or higher

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