Senior Software Engineer (AI)

Location: Remote

Company

hirify.global is building a privacy-centric platform for the secure and efficient exchange of AI training data, connecting organizations with valuable data to AI builders.

What you will do

• Design, build, and operate ingestion systems that transform large-scale imaging, audio, video, text, and other multimodal data into structured, AI-ready datasets.
• Own ingestion pipelines end to end, including data landing, validation, processing, tracking, provenance, and downstream delivery.
• Build parsers, validators, normalization logic, modality-specific processing, and reusable internal tooling for messy and non-standard source formats.
• Scale distributed and parallel processing systems for millions to billions of records and source objects while optimizing reliability, cost, and speed.
• Implement data quality checks, observability, debuggability, and operational reliability across the ingestion layer.
• Partner with product, Data Lab, and partner engineering teams to support new modalities and translate source-system requirements into robust designs.

Requirements

• 5+ years building and operating production backend or data systems, including data processing at scale.
• Hands-on experience designing and running large-scale data pipelines and distributed data processing systems.
• Strong programming skills in Python.
• Strong proficiency with AWS.
• Ability to work with messy, varied, high-volume data and ambiguous problem spaces while maintaining attention to detail and delivery speed.
• Curiosity, tenacity, proactivity, and a bias toward action.

Nice to have

• Experience processing medical imaging, text, audio, or video at scale.
• Experience with sensitive or regulated data, including HIPAA, healthcare compliance, PHI handling, and de-identification.
• Experience with streaming systems or workflow orchestration such as Airflow or Dagster.
• Experience with GCP, Azure, startup engineering, ML, NLP, or LLM-based systems.

Culture & Benefits

• Remote work in a lean, fast-moving, high-trust engineering environment.
• Ownership, accountability, velocity, and measurable impact are emphasized.
• Collaboration across engineering, product, Data Lab, and partner teams.
• Culture values integrity, resourcefulness, kindness, candor, and continuous improvement.
• Opportunity to work on secure, privacy-centric AI data infrastructure across healthcare, media, and other industries.