Навыки и технологии
О роли
We are seeking a highly skilled Generative AI Operations Engineer (GenAI Ops) to join our cutting-edge AI team. The ideal candidate will have strong expertise in operationalizing large-scale generative AI systems, building CI/CD pipelines, and managing AI agent infrastructures across cloud environments. You will play a key role in ensuring the scalability, security, and performance of multi-agent AI systems and generative applications.
Responsibilities
- Design, implement, and maintain automated CI/CD pipelines for the development, training, and deployment of Large Language Models (LLMs) and AI agents
- Build and manage agentic AI systems, ensuring efficient agent-to-agent collaboration and orchestration of complex workflows
- Integrate AI agents with external tools and APIs using modern standards such as the Model Context Protocol (MCP)
- Leverage AI-powered development tools to streamline software delivery, infrastructure management, and troubleshooting processes
- Define and manage cloud infrastructure for GenAI workloads using Infrastructure as Code (IaC) tools such as Terraform, AWS CDK, or CloudFormation
- Implement monitoring and observability solutions for models, agents, and system health using tools like Prometheus, Grafana, or Datadog
- Optimize scalability, performance, and cost-efficiency of GenAI services in production environments
- Enforce AI security, safety, and governance practices, ensuring compliance with organizational and industry standards
Requirements
- Minimum 3 years of experience in DevOps, Site Reliability Engineering (SRE)
- Minimum 1 year of experience in MLOps roles with a strong focus on cloud infrastructure
- Proven experience with AWS, Google Cloud, or Azure
- Proficiency in Python or Bash, and experience with containerization/orchestration tools such as Docker and Kubernetes
- Strong background in building and maintaining CI/CD pipelines using Jenkins, GitLab CI, or similar tools
- Experience with cloud-native GenAI platforms (e.g., AWS Bedrock, Azure AI Foundry, Google Vertex AI)
- Familiarity with LLM architectures and the challenges of deploying large-scale models
- Experience designing or managing multi-agent systems and orchestrated AI workflows
- Hands-on experience implementing infrastructure using IaC frameworks
- B2+ level of English proficiency
Nice to have
- Master’s or PhD in Computer Science, AI, or related field
- Relevant cloud or DevOps certifications (e.g., AWS Certified DevOps Engineer, Google Cloud Professional DevOps Engineer)
- Strong problem-solving mindset and ability to thrive in a fast-paced, innovative environment
О компании
EPAM (NYSE:EPAM) is a global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. With over thirty years of expertise in custom software, product and platform engineering, EPAM empowers organizations to become AI-native enterprises, driving measurable value from innovation and digital investments. Recognized by industry benchmarks and leading analysts as a leader in AI, EPAM delivers globally while engaging locally, making the future real for clients, partners and employees.
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