Lead AI Engineer with AWS Bedrock
Why This Role Stands Out
This hybrid Lead AI Engineer role at EPAM Systems offers a fantastic opportunity to drive innovation in AIOps using cutting-edge AWS Bedrock technology, perfect for experienced engineers eager to shape impactful GenAI solutions. You'll thrive in this collaborative environment, leveraging your Python/TypeScript and AWS expertise to build and deploy scalable AI services, all while enjoying the flexibility of a hybrid work model. Apply now to advance your career at a leading technology company!
Quick Overview
Job Description
We are seeking a hands-on Lead AI Engineer focused on building and deploying AIOps solutions using AWS Bedrock and agent-based architectures. The role requires strong engineering capability in Python or TypeScript combined with real-world experience implementing GenAI-powered systems in cloud environments.
Responsibilities Design and implement AIOps solutions leveraging AWS Bedrock and agent-based architectures Build, deploy, and maintain AI services using Python or TypeScript Develop and manage infrastructure using AWS CDK Integrate GenAI capabilities into operational systems, including monitoring, automation, and incident handling Collaborate with cross-functional teams to deliver production-ready AI features Ensure scalability, reliability, and performance of deployed solutions Requirements 5+ years of hands-on engineering experience delivering production-grade solutions (not only prototypes or POCs) At least 1 year of relevant leadership experience Proven expertise in AWS Bedrock (including AgentCore) applied in real projects Proficiency in Python or TypeScript Skills in building and deploying infrastructure using AWS CDK Understanding of DevOps practices, including CI/CD, deployment, and monitoring Background in AIOps or observability platforms Strong communication skills for effective team collaboration Proficiency in English at an Upper-Intermediate level (B2) or higher Nice to have Background in Generative AI and LLM-based solutions Experience working in distributed or customer-facing teams Familiarity with the broader AWS ecosystem, such as Lambda, ECS, etc.
Skills
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