Applied AI & Data Engineer, Business & Education

What you'll do

• Design and build data and AI platforms on Databricks and AWS using modern cloud-native patterns.
• Own AI and agentic systems end-to-end, including retrieval, planning, evaluation, guardrails, and deployment.
• Build RAG pipelines, vector search, knowledge graphs, and multi-agent orchestration for natural-language data interfaces.
• Optimize systems for scale by managing model selection, latency, throughput, and token economics.
• Translate ambiguous requirements from stakeholders into secure, scalable, and production-ready systems.
• Provide technical leadership through design reviews, implementation guidance, and production-readiness checks.
• Mentor engineers and develop technical playbooks to help the team adopt AI-native practices.
• Research and implement state-of-the-art data and AI techniques to accelerate pipeline development and analytics.

What we're looking for

• 8+ years of experience in data, analytics, software, or ML engineering.
• 3+ years of experience building and shipping Applied AI and agentic LLM systems in production.
• BS or MS in Computer Science, Information Systems, AI, Machine Learning, Engineering, Mathematics, Statistics, or a related field (or equivalent experience).
• Hands-on fluency with LLM frameworks (LangChain, LlamaIndex, etc.), vector search, RAG pipelines, and multi-agent coordination.
• Proficiency in at least one high-level language (Python, Scala, Java, or Go) and strong SQL skills.
• Experience designing scalable data platforms on modern cloud-native patterns like Databricks and AWS.
• Experience delivering ETL/ELT, streaming, and CDC pipelines using Spark, Kafka, and Delta Lake.
• 3+ years of experience mentoring engineers and providing hands-on technical leadership.