Senior AI Engineer

Location: Remote in Germany, Ireland, the Netherlands, Portugal, Spain, or the United Kingdom

Company

hirify.global builds forms, surveys, and quizzes that help businesses collect data through human-centered digital experiences.

What you will do

• Design, build, and deploy generative AI capabilities across hirify.global products.
• Develop AI applications using large language models, RAG, vector search, and agentic systems.
• Build Python services, APIs, machine learning workflows, and real-time or batch processing pipelines.
• Design automated evaluation pipelines and benchmarks covering accuracy, relevance, reliability, fairness, latency, and cost.
• Operate and improve AI systems through monitoring, observability, security safeguards, and performance optimization.
• Establish reusable 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 built with frameworks such as FastAPI.
• Experience developing generative AI applications with large language models, RAG, tool use, or agentic systems.
• Experience with PyTorch, LangChain, LangGraph, or similar technologies, plus enterprise RAG concepts including chunking, embeddings, retrieval, reranking, evaluation, and monitoring.
• Experience with AWS, Docker, Kubernetes, Terraform, CI/CD, SageMaker or Bedrock, Kafka, vector databases, and MLflow.
• 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 similar 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 latency and cost for AI systems operating at scale.

Culture & Benefits

• Cross-functional collaboration across Product, Engineering, Data Science, Data Engineering, and Analytics.
• Emphasis on transparency, trust, respect, diversity, and inclusive collaboration.
• Focus on high standards, customer needs, and dependable product experiences.
• Equal-opportunity workplace with a commitment to preventing discrimination and harassment.