Generative AI Operations Engineer (GenAI Ops)

EPAM Systems; Turkey; On-site; TRY 2,874,000 - 4,789,000; Full time

Benefits offered by this job

Continuous upskilling

Private health insurance

English courses

Mentoring programs

Access to learning platforms

Internal courses (2,500+)

Job summary

EPAM Systems in Turkey seeks a Generative AI Operations Engineer to design, deploy, and maintain the backbone for GenAI models and services. You will collaborate with data scientists, ML engineers, and software developers to ensure scalable, reliable AI applications across leading cloud platforms.

You will build CI/CD pipelines for LLMs, deploy multi-agent systems, integrate with external tools, and apply IaC like Terraform while monitoring performance and security.

Qualifications

• Bachelor’s degree in Computer Science or a related field or equivalent practical experience.
• 3+ years in DevOps, SRE, or MLOps focusing on cloud infrastructure.
• Hands-on experience with AWS, Google Cloud, or Azure.
• Strong background building CI/CD pipelines (Jenkins, GitLab CI, etc.).
• Proficiency in Python or Bash scripting.
• Experience with IaC tools (AWS CDK, CloudFormation, Terraform).
• Familiarity with GenAI services (Bedrock, Vertex AI, etc.).
• Understanding of LLM architecture and operational challenges.
• Experience with Hugging Face, OpenAI, or LangChain frameworks.
• Monitoring/observability tools (Prometheus, Grafana) and ML experiment tracking (MLflow).
• Containerization and orchestration (Docker, Kubernetes).
• Fluent English communication (B2+).

Responsibilities

• Design, implement, and maintain automated CI/CD pipelines for training, evaluating, and deploying LLMs and AI agents.
• Deploy and manage multi-agent AI systems with secure agent communication and collaboration.
• Integrate AI agents with external tools via Model Context Protocol for interoperability and security.
• Use AI-powered tools to accelerate infrastructure code, testing, and troubleshooting in cloud environments.
• Define and manage GenAI infrastructure using IaC tools such as Terraform.
• Implement monitoring and logging to track model/agent performance, resource usage, and health.
• Design scalable architectures for model serving and inference focusing on performance and cost.
• Apply security best practices and ensure regulatory compliance for GenAI infrastructure and data.

Skills

Cloud platforms

CI/CD pipelines

Terraform

Python/Bash

IaC tools

GenAI services

LLMs

Docker & Kubernetes

Monitoring & observability

English communication

Education

Bachelor’s degree in Computer Science or related field

Tools

Jenkins

GitLab CI

AWS CDK

CloudFormation

Terraform

Docker

Kubernetes

Prometheus

Grafana

MLflow

Job description

We are seeking a highly motivated and experienced Generative AI Operations (GenAI Ops) Engineer to join our forward-thinking team.

In this position, you will play a key role in building, deploying, and maintaining the operational backbone for advanced generative AI models and services. You will collaborate with data scientists, machine learning engineers, and software developers to ensure our GenAI applications—including complex, multi-agent systems—are scalable, reliable, and efficient across leading cloud platforms. If you are passionate about operationalizing large-scale AI systems and eager to make a meaningful impact, we want to hear from you.

Responsibilities

• Design, implement, and maintain automated CI/CD pipelines for training, evaluating, and deploying large language models (LLMs) and AI agents
• Deploy and manage sophisticated multi-agent AI systems, ensuring seamless agent-to-agent communication and collaboration for automating complex business processes
• Integrate AI agents with external tools and APIs, using open standards like Model Context Protocol (MCP) to ensure interoperability and security
• Utilize AI-powered development tools to accelerate infrastructure code, testing, and troubleshooting in cloud environments
• Define and manage GenAI infrastructure using cloud-native or cloud-agnostic Infrastructure as Code (IaC) tools such as Terraform
• Implement monitoring and logging solutions to track model and agent performance, resource usage, and system health, including tracing agent actions and multi-step conversational flows
• Design and optimize scalable architectures for model serving and inference, focusing on performance and cost-effectiveness
• Apply security best practices and ensure compliance with industry standards and regulations for GenAI infrastructure and data

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
• At least 3 years of experience in a DevOps, SRE, or MLOps role with a focus on cloud infrastructure
• Hands‑on experience with cloud services from major providers such as AWS, Google Cloud, or Azure
• Strong background in building and managing CI/CD pipelines using tools like Jenkins, GitLab CI, or cloud‑native solutions
• Proficiency in at least one scripting language such as Python or Bash
• Experience with Infrastructure as Code (IaC) tools like AWS CDK, CloudFormation, or Terraform
• Familiarity with cloud‑native GenAI services such as AWS Bedrock, Azure AI Foundry, or Google Vertex AI
• Understanding of the architecture and operational challenges of Large Language Models (LLMs)
• Practical experience with generative AI frameworks including Hugging Face, OpenAI, or LangChain
• Experience with monitoring and observability tools for AI/ML systems such as Prometheus or Grafana
• Experience with ML experiment tracking and versioning tools like MLflow or Weights & Biases
• Hands‑on experience with containerization and orchestration technologies such as Docker and Kubernetes
• Fluent English communication skills at a B2+ level

Nice to have

• Master’s degree or PhD in Computer Science, AI, Machine Learning, or a related discipline
• Experience designing or managing multi-agent systems or orchestrated AI workflows
• Relevant certifications in cloud or DevOps technologies
• Strong analytical and problem‑solving skills with the ability to thrive in a fast‑paced, collaborative environment

We offer

• CONTINUOUS UPSKILLING, LEARNING & DEVELOPMENT
  • Diversity of tasks and projects
  • Assessment center for objective review of competency level
  • Personal development plan
  • Mentoring programs and leadership development
  • Certification and professional development support
  • Access to learning platforms including more than 2,500 internal courses
  • English courses taught by certified teachers
• CORPORATE BENEFITS
  • Extra leave days
  • Referral bonuses
• COMPENSATION PACKAGE
  • Competitive compensation paid in USD
  • Regular salary and performance reviews
• MEDICAL & HEALTHCARE
  • Private health insurance
  • Well‑being events
• WORKING ENVIRONMENT
  • Recreation areas and kitchens
  • Tea, coffee and snacks
  • Sports equipment and game consoles
  • IT Equipment
  • Microsoft’s Software Assurance Home Use Program (HUP)

Please note that our Talent Attraction Team reviews applications and CVs submitted in English.

EPAM is 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, we empower our clients to become AI-Native enterprises, driving measurable value from innovation and digital investments.