Software Engineer I (AI)

Location: Seattle, WA, with relocation to Seattle, WA or San Jose, CA required if not currently based in one of these locations; hybrid work with periodic in-office collaboration in Seattle

Annual base pay: $105,600–$158,400

Company

hirify.global develops cybersecurity and digital solutions that help organizations create, secure, and run applications.

What you will do

• Contribute to software projects across the full development cycle, from requirements analysis through implementation and testing.
• Design, implement, test, and integrate APIs, services, and application components with mentorship from senior engineers.
• Develop data-driven solutions using machine learning and AI technologies.
• Participate in design and code reviews and create technical documentation for designs and features.
• Collaborate with engineers and peers to deliver solutions aligned with project goals.

Requirements

• Bachelor’s degree in computer science, software engineering, information technology, computer engineering, or a related field.
• Programming experience in Python, Java, C++, or Go, including APIs or services, tests, and Git-based collaboration.
• Hands-on exposure to machine learning and deep learning concepts, including PyTorch, TensorFlow, or JAX; training, inference, and basic model evaluation.
• Familiarity with LLM tooling and patterns, including Hugging Face Transformers, prompt engineering, and retrieval-augmented generation.
• Exposure to ML data formats and pipelines such as Parquet, ETL, and data quality checks, plus computer science fundamentals.
• Must be willing to relocate to Seattle, WA or San Jose, CA if not currently based in one of these locations.

Nice to have

• API and backend experience with FastAPI, Flask, REST, gRPC, authentication, pagination, and error handling.
• Experience with retrieval-driven AI applications, LangChain, LlamaIndex, and vector search technologies.
• Familiarity with fine-tuning, ML experimentation, containers, Kubernetes, CI/CD, and observability.
• Experience with Spark, Ray, Kafka, or Airflow in distributed ML workloads.

Culture & Benefits

• Hybrid work with periodic in-office collaboration in Seattle.
• Health, wellness, and retirement benefits.
• Training, mentorship, and ongoing professional development.
• Flexible work arrangements and work-life balance benefits.
• Employee resource groups and an inclusive, people-first community.