AI Engineer
New
U
UnivioAI Solutions
Wrocław, Strzegomska 2/4, Kraków, AK 25, Warszawa, -, Poznań, -, Łódź, -, Gdańsk, -, Katowice, -, Wrocław, Country code: PLContractSenior
Salary20,160 - 28,560 PLN per hour
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Job Details
- Languages
- Pl C1, en B2
- Required Skills
- AWSDockerPythonArtificial IntelligenceGitJavascriptKubernetesAzureCI/CDLLM
Requirements
- Proven experience in creating backend solutions and integrating systems via APIs.
- Practical knowledge of AI/LLM models, prompts, context management, token handling, and cost constraints.
- Experience integrating with AI models such as OpenAI, Azure OpenAI, Gemini, Claude, or open-source equivalents.
- Ability to design and develop AI agents, automation tasks, and agent pipelines.
- Proficiency in Docker and Docker Compose for managing local or isolated development environments.
- Strong skills in Git for code review, conflict resolution, refactoring, and quality maintenance.
- Ability to diagnose technical issues across applications, logs, integrations, databases, and runtime environments.
- Understanding of CI/CD, containerization, and management of testing and production environments.
- Ability to collaborate across developer, DevOps, analytical, and business teams.
- Commitment to security, access control, license compliance, and responsible AI usage.
Responsibilities
- Develop and maintain AI agent-based tools, workspace configurations, and agent pipelines.
- Integrate applications with LLMs and develop intermediary layers such as AI Gateways or proxies.
- Build backends for AI applications, handling document indexing and processing (PDF, DOCX, XLSX, CSV, Markdown).
- Create integrations with enterprise tools including Jira, SharePoint, Power BI, Grafana, and n8n.
- Prepare and maintain development environments using Docker and Docker Compose.
- Collaborate on deployment processes, application configuration, CI/CD pipelines, and Kubernetes environments.
- Monitor AI model usage (tokens, costs, metrics) and manage Grafana dashboards.
- Test new AI models, including open-source options, for quality and deployment viability.
- Optimize AI costs through caching, proxies, prompt compression, and token management.
- Perform code reviews, refactoring, and maintain repository quality and documentation.
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