Applied AI Engineer (AI)

TL;DR

Applied AI Engineer (AI): Architecting and deploying enterprise-grade AI solutions and AI agents using hirify.global AI Platform and Cortex with an accent on production-grade AI systems and scalable ML pipelines. Focus on solving complex business challenges for strategic customers, optimizing LLM performance, and implementing RAG and agentic workflows.

Location: PL-Warsaw

Company

A global leader in AI-native data cloud technology powering the agentic enterprise.

What you will do

• Architect, build, and deploy enterprise-grade AI solutions and sophisticated AI agents.
• Own the end-to-end lifecycle from prototype to production for strategic customers.
• Design and iterate high-quality code and ML pipelines using Python and SQL.
• Serve as a strategic technical advisor to customer data science and engineering teams.
• Implement rigorous data validation and SLA observability for reliable AI performance.
• Collaborate with Product and Engineering teams to influence the future of the AI platform.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• 3+ years of professional software engineering experience.
• Experience building and tuning applications involving ML models or data-intensive systems.
• Advanced proficiency in Python and experience with data modeling and ETL/ELT.
• Familiarity with data science libraries like pandas, numpy, and Snowpark.
• Strong communication skills for articulating technical concepts to diverse stakeholders.

Nice to have

• Experience productionizing applications using LLMs, RAG, and agentic workflows.
• Hands-on experience with the MLOps lifecycle in cloud environments (AWS, Azure, or GCP).
• Strong understanding of data warehousing principles and architecture.
• Previous experience in customer-facing roles, such as a Solutions Architect.
• Startup experience.

Culture & Benefits

• Opportunity to work with cutting-edge AI tools and infrastructure at scale.
• Fast-paced, dynamic environment with an experimental mindset.
• Direct impact on the future of AI and data cloud technology.
• Collaborative environment with high-trust AI-native thinkers.