8 дней назад
Forward Deployed Engineer (Applied AI)
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
Forward Deployed Engineer (Applied AI) (Python/SQL/LLM): Building and deploying production-grade enterprise AI systems, agents, and ML pipelines for strategic customers with an accent on scalable implementation, data workflows, and customer-facing technical delivery. Focus on productionizing LLM applications, designing evaluation and observability frameworks, and solving complex system reliability challenges in large-scale environments.
Location: Warsaw, Poland; on-site
Company
Snowflake develops AI and data cloud technology, including the Snowflake AI Platform and Cortex AI capabilities.
What you will do
- Architect, build, and deploy enterprise-grade AI solutions, including AI agents, from prototype to production.
- Design and iterate on AI pipelines and production-quality software using Python and SQL.
- Own the implementation lifecycle for AI solutions, including deployment, monitoring, optimization, and operational reliability.
- Partner with customer data science and engineering teams as a technical advisor.
- Implement data validation, SLA observability, and management of complex system interdependencies.
- Collaborate with Product and Engineering teams to improve Snowflake’s AI platform based on customer feedback.
Requirements
- Bachelor’s degree in Computer Science, Engineering, a related technical field, or equivalent practical experience.
- 3+ years of professional software engineering experience.
- Hands-on experience building and shipping LLM-based or machine learning applications.
- Experience with data modeling, ETL/ELT development, performance tuning, and automated data workflows.
- Advanced proficiency in Python, Java, C++, or another backend programming language.
- Strong problem-solving, communication, and adaptability skills for complex and ambiguous technical challenges.
Nice to have
- Production experience with LLMs, RAG, or agentic workflows.
- Experience with the MLOps lifecycle, including model deployment, monitoring, and evaluation in AWS, Azure, or GCP.
- Strong knowledge of data warehousing architecture and best practices.
- Customer-facing experience, such as solutions architecture, and startup experience.
Culture & Benefits
- Opportunity to work on enterprise AI and data cloud technology at scale.
- Access to Snowflake’s AI capabilities and infrastructure.
- Progressive ownership from individual components to workstreams and customer engagements.
- Growth milestones include independently running a scoped customer working session and owning a workstream end to end.
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