Fullstack AI Engineer (AI)

TL;DR

Fullstack AI Engineer (AI): Building the next generation of tools for developing, evaluating, and training state-of-the-art AI systems with an accent on human-in-the-loop systems and high-throughput review interfaces. Focus on designing end-to-end features, architecting scalable data layers for LLM pipelines, and enabling robust evaluation frameworks across various data modalities.

Location: Hybrid model with 2 days per week in office in San Francisco, USA or Wrocław, Poland.

Salary: $130,000–$200,000 USD

Company

hirify.global is a data-centric AI infrastructure company providing integrated platforms for data annotation, model evaluation, and expert labeling services.

What you will do

• Design, build, and ship complete end-to-end workflows spanning frontend UI, APIs, backend services, and production infrastructure.
• Develop systems that enable efficient human-in-the-loop training for RLHF and preference data pipelines.
• Create high-throughput, reviewer-focused interfaces using React optimized for data quality control and operational workflows.
• Architect scalable backend services and data schemas that support large-scale iteration with strong guarantees around correctness.
• Leverage LLMs to build automated quality checks, ranking suggestions, and critiques within the human review loop.
• Participate in on-call rotations to ensure system reliability across the full stack.

Requirements

• Bachelor’s degree in Computer Science, Data Engineering, or related field.
• Minimum of 2 years of experience in a software or machine learning engineering role.
• Proficiency with frontend frameworks like React and backend technologies like Python, Java, or Node.
• Experience designing and managing scalable database systems such as PostgreSQL or NoSQL stores.
• Experience with cloud infrastructure and containerization technologies like Kubernetes.
• Ability to write clean, well-tested code in a fast-paced environment.

Nice to have

• Experience building tools for AI/ML applications, specifically data annotation or model evaluation.
• Familiarity with data infrastructure, including data pipelines, streaming systems, and search engines like ElasticSearch.
• Strong background in database performance optimization, including schema design and query tuning.

Culture & Benefits

• High-impact environment focused on ownership and rapid iteration.
• Opportunity to shape the future of AI infrastructure while collaborating with industry-leading AI labs.
• Clear ownership of product features with autonomy in execution.
• Support for professional growth and continuous learning at the frontier of technology.
• Hybrid work arrangement providing flexibility combined with intentional in-office collaboration.