Applied AI & Data Engineer - Business & Education

What you'll do

• Design and build cloud data and AI platforms, data models, pipelines, and quality practices.
• Own AI and agentic systems from retrieval and evaluation through deployment, guardrails, and operations; optimize cost, latency, and throughput.
• Lead projects and mentor engineers while partnering across teams to deliver secure, production-ready capabilities.

What they ask for

• 8+ years across data, analytics, software, or ML engineering, including the last 3+ years building and shipping production Applied AI and agentic LLM systems.
• Hands-on experience with production AI/LLM systems, RAG, agent frameworks, vector search, evaluation, guardrails, and system optimization.
• Experience building scalable data platforms and ETL/ELT, streaming, and CDC pipelines; proficiency in at least one of Python, Scala, Java, or Go, plus strong SQL.
• 3+ years mentoring engineers and prioritizing concurrent initiatives; BS or MS in a related field, or equivalent practical experience building data and AI systems in production.

Nice to have

• Fine-tuning, reward models, custom retrieval or embedding models, or prompt customization at scale.
• MLOps/LLMOps, natural-language data interfaces, AI-assisted development, or experience in regulated or privacy-sensitive environments.

Pay

$184,700 and $324,800 USD base salary; $175,000 and $308,500 USD base salary

Tools

Databricks, AWS, LangChain, LlamaIndex, Semantic Kernel, Google ADK, pgvector, FAISS

AI focus

Build production GenAI and agentic systems, including RAG, vector search, knowledge graphs, multi-agent orchestration, natural-language data interfaces, evaluation, and AI-native workflow capabilities.