Back to Search
Generative AI Operations Engineer (GenAI Ops)
Remote in Georgia, & 5 others
Generative AI Operations
apply
FacebookLinkedInSend via email
Looking for something else?
Find a vacancy that works for you. Send us your CV to receive a personalized offer.
Find me a job
Location-specific conditions & benefits*
Choose an option
We are seeking a highly motivated and experienced Generative AI Operations (GenAI Ops) Engineer to join our innovative team.
In this role, you will be at the forefront of the AI revolution, responsible for building, deploying, and maintaining the operational infrastructure for our cutting-edge generative AI models and services. You will work closely with data scientists, machine learning engineers, and software developers to ensure our GenAI applications - especially complex, multi-agent systems - are scalable, reliable, and efficient across major cloud platforms. If you are passionate about operationalizing large-scale AI systems and want to make a significant impact, this is the role for you.
Responsibilities
Build and Manage CI/CD Pipelines: Design, implement, and maintain robust, automated CI/CD pipelines for training, evaluating, and deploying large language models (LLMs) and AI agents
Orchestrate Agentic AI Workflows: Design, deploy, and manage sophisticated, multi-agent systems. Ensure seamless Agent-to-Agent (A2A) communication and collaboration between specialized agents to automate complex business processes
Manage Tool Integration: Implement and manage secure, scalable integrations between AI agents and external tools/APIs, leveraging open standards like the Model Context Protocol (MCP) to ensure interoperability
Leverage AI-Powered Development: Utilize AI-powered development tools to accelerate the entire software development lifecycle, from writing infrastructure code and tests to troubleshooting operational issues in cloud environments
Infrastructure as Code (IaC): Utilize cloud-native IaC services or cloud-agnostic tools like Terraform to define and manage the infrastructure required for GenAI workloads
Model Monitoring and Observability: Implement comprehensive monitoring and logging solutions to track model and agent performance, resource utilization, and system health. For agentic systems, this includes tracing the agents actions and logging the multi-step conversational flow
Scalability and Performance Optimization: Design and implement scalable architectures for model serving and inference. Continuously optimize the performance and cost-effectiveness of our GenAI services
Security and Compliance: Implement and enforce security best practices for our GenAI infrastructure and data. Ensure compliance with industry standards and regulations
Requirements
Bachelors degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
3+ years of experience in a DevOps, SRE, or MLOps role with a focus on cloud infrastructure
Proven experience with cloud services from major providers like AWS, Google Cloud, or Azure
Strong experience building and managing CI/CD pipelines using tools like Jenkins, GitLab CI, or cloud-native services
Proficiency in at least one scripting language (e.g., Python, Bash)
Hands-on experience with Infrastructure as Code (IaC) tools such as AWS CDK, CloudFormation, or Terraform
Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes)
Fluent English communication skills at a B2+ level
Nice to have
Masters degree or PhD in Computer Science, AI, Machine Learning, or a related field
Experience with cloud-native GenAI services like AWS Bedrock, Azure AI Foundry, or Google Vertex AI
Familiarity with the architecture and operational challenges of Large Language Models (LLMs)
Experience designing or managing multi-agent systems or complex, orchestrated workflows
Knowledge of monitoring and observability tools like Prometheus, Grafana, or Datadog
Relevant cloud or DevOps certifications
Strong problem-solving skills and the ability to work effectively in a fast-paced, collaborative environment