12 часов назад
Middle AI Engineer (GenAI Deployment)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Middle AI Engineer (GenAI Deployment) (Azure, AWS, Docker): Productionizing and deploying GenAI agents, MCP servers, and prediction-serving APIs in client cloud environments with an accent on containerization, CI/CD, and cloud infrastructure. Focus on configuring Azure ML workspaces, troubleshooting compute capacity, implementing observability, and documenting reliable deployment architectures.
Location: Lviv, Ukraine
Company
Robots & Pencils is an applied AI engineering firm building and deploying AI co-workers and enterprise AI systems for clients across multiple industries.
What you will do
- Productionize and deploy GenAI agents into client cloud environments, using Azure as the primary platform and AWS for selected components.
- Own MCP server architecture and deployment, including hosting decisions, Docker-based containerization, and resilience improvements.
- Containerize and deploy FastAPI-style prediction-serving APIs that wrap machine learning models.
- Set up CI/CD pipelines for agent and API deployments in GitHub Enterprise.
- Configure Azure ML workspaces, provision compute, troubleshoot quotas and capacity, and manage access.
- Implement logging, health checks, alerting, and deployment architecture documentation.
Requirements
- 3+ years of professional software engineering experience with hands-on exposure to AI/ML systems and generative AI development.
- Strong software engineering fundamentals and experience with Python or a similar language.
- Hands-on Docker and containerization experience, including designing deployment architectures from scratch.
- Experience with Azure services such as App Service, Container Apps, and ML workspaces, and/or AWS services including EC2 and ECS.
- Production experience deploying and operating LLM-based agents or GenAI applications.
- Familiarity with MCP or comparable agent-tool orchestration patterns, CI/CD, GitHub Enterprise, Azure AD/SSO, and enterprise client environments.
Nice to have
- MLOps experience with model versioning, drift monitoring, or retraining pipelines.
- Azure SQL or data-engineering-adjacent experience.
- Consulting or client-services experience and comfort with ambiguity and shifting scope.
- Experience building demand-prediction models from historical data.
Culture & Benefits
- 20 days of paid vacation and 15 days of unpaid vacation.
- All official public holidays off and 5 paid sick days without a doctor’s certificate.
- Medical insurance.
- Military draft deferment and reservation support.
- Cooperation under a gig-contract.
- Remote-friendly and collaborative environment with cross-functional engineering, design, and strategy teams.
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