We are looking for an AI Engineer with a strong foundation in machine learning (ML), data engineering, or both, and hands-on experience building modern AI systems. This role is best suited for someone who started their career in ML, applied modeling, data engineering, or software engineering for data-intensive systems and later expanded into large language models (LLMs), retrieval-augmented generation (RAG), and agentic AI systems. We are looking for someone with an evaluation-first mindset who believes AI systems should be designed with clear success criteria, testing strategies, and monitoring plans from the start.
The ideal candidate brings strong ML or data systems fundamentals, experience building LLM-powered applications, and practical experience designing and operating production-grade AI solutions that solve real business problems. This includes:
Building multi-step AI workflows
Integrating AI into enterprise systems
Balancing quality, latency, cost, reliability, and maintainability
Humility, accountability, and a growth mindset are essential for success in this role. The right candidate is comfortable admitting mistakes, learning from feedback, challenging assumptions, and adjusting quickly when evidence suggests a better path forward.
Qualifications
Bachelor's degree in Computer Science or a related field
6+ years of relevant experience
4+ years of experience in one or more of the following areas:
Machine Learning or Applied Modeling
Data Engineering
Software Engineering for Data-Intensive Systems
2+ years of experience building LLM-based applications, including at least 1 year building agentic AI systems
Experience building and operating production data pipelines, data platforms, or large-scale data-intensive systems
Hands-on experience building LLM-powered applications, including:
Context engineering
Retrieval-augmented generation (RAG)
Evaluation frameworks
Prompt engineering and optimization
Experience designing and implementing agentic AI systems, including multi-step workflows
Strong track record of defining evaluation strategies upfront and operating AI systems in production
Advanced Python skills
Requirements
Evaluation-first mindset
Thoughtful, practical, and systems-oriented
Ownership of outcomes and learning from mistakes
Comfortable working in ambiguity and collaborating across teams
Benefits
Competitive salary ranges aligned to industry standards
Up to a 10% annual incentive bonus
Comprehensive benefits package, including:
Universal, supplemental, and private healthcare plan choices
Retirement/pension plan contributions
Life event & disability coverage
Generous annual leave, company holidays, volunteer time off