Senior AI Engineer (AI)

Location: Remote in the United States; candidates must be based in the ET timezone.

Company

hirify.global is a form builder that helps businesses collect data through forms, surveys, and quizzes, including AI-powered research experiences.

What you will do

• Design, build, and deploy generative AI capabilities for Research Flow and other hirify.global products.
• Develop AI applications using large language models, RAG, vector search, and agentic systems.
• Build APIs, machine learning services, and batch or real-time pipelines with Python, AWS, Docker, Kubernetes, Kafka, Airflow, and MLflow.
• Turn prototypes into secure, reliable production systems with strong performance, scalability, observability, and cost efficiency.
• Create automated evaluations and benchmarks for accuracy, relevance, reliability, fairness, latency, and cost.
• Establish AI engineering standards and collaborate with Product, Engineering, Data Science, Data Engineering, and Analytics teams.

Requirements

• At least four years of experience building and deploying machine learning or AI systems in production.
• Strong Python and software engineering skills, including production services with frameworks such as FastAPI.
• Practical experience with generative AI, large language models, RAG, tool use, or agentic systems.
• Experience with PyTorch, LangChain, LangGraph, enterprise retrieval systems, automated AI evaluations, and vector databases.
• Experience with AWS, Docker, Kubernetes, Terraform, CI/CD, SageMaker or Bedrock, Kafka, MLflow, and production monitoring tools.
• Strong communication skills and the ability to balance quality, speed, reliability, scalability, and cost.

Nice to have

• Experience in a B2B SaaS product company.
• Experience with Airflow, Argo Workflows, SQL, Spark, Snowflake, or other data-processing technologies.
• Experience combining structured data, unstructured data, and generative AI.
• Experience with AI security, privacy, responsible AI, prompt-injection protection, or data-leakage prevention.
• Experience improving the latency and cost of AI systems at scale.

Culture & Benefits

• Fully remote work designed around distributed collaboration.
• Cross-functional work with Product, Engineering, Data Science, Data Engineering, and Analytics teams.
• Focus on respect, transparency, trust, diversity, and inclusive collaboration.
• Equal-opportunity workplace with a commitment to preventing discrimination and harassment.