обновлено 1 месяц назад
AI Engineer (Agentic Workflows)
2 600€
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Engineer (Agentic Workflows) (Generative AI/Python): Designing and operating production generative AI systems and end-to-end agentic workflows with an accent on LLM orchestration, evaluation, observability, and cost optimization. Focus on integrating multiple LLMs, building reliable data flows and guardrails, and leading architecture and production deployment decisions.
Location: Bratislava, Slovakia; hybrid schedule with occasional home office possible.
Starting base salary: €2,600.
Company
provides insurance services and supports an open-minded, safe, and inclusive working environment.
What you will do
- Design, build, and own end-to-end agentic workflows using LangGraph or similar frameworks.
- Translate ambiguous business needs into scalable technical solutions and architecture decisions.
- Develop production-grade agents, tools, and reusable components with interfaces, tests, and documentation.
- Integrate multiple LLM providers and optimize systems for latency, cost, and quality.
- Establish evaluation metrics, datasets, guardrails, logging, monitoring, and incident response practices.
- Collaborate with product, data, and engineering teams while mentoring junior engineers.
Requirements
- 2–4 years of professional experience in software engineering, data science, or AI engineering.
- At least 2 years of hands-on experience building production generative AI systems.
- Strong Python skills and software engineering fundamentals, including testing, CI/CD, and code review.
- Production experience with LLM systems, advanced prompting, API integration, and workflow orchestration.
- Experience with LangGraph or similar agentic frameworks such as LangChain, CrewAI, AutoGen, or custom orchestration.
- Experience leading technical initiatives and making architecture decisions with an understanding of trade-offs.
Nice to have
- Experience with AI coding assistants, LLM observability platforms, vector databases, and RAG architectures.
- Knowledge of LLM cost optimization, token management, async Python, and concurrent request handling.
- Experience deploying AI systems on Azure, AWS, or GCP using cloud-native architectures.
- Familiarity with evaluation frameworks, fine-tuning, prompt optimization, or model selection.
Culture & Benefits
- Personal days off, additional vacation, a concentrated work week, home-office flexibility, sabbatical leave, and workation.
- Life insurance, sick-leave salary-loss compensation, third-pillar pension contributions, meal contributions, and service bonuses.
- Wedding and baby bonuses, maternity leave benefits, an electronic cafeteria, and office massages.
- Professional certifications, online education portals, extensive onboarding, and a strengths-based culture.
- Opportunities to lead increasingly complex initiatives and grow toward senior or staff engineer roles.
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