Senior AI Product Engineer
Citian · Washington D.C.
About this role
Citian is a fast-growing, venture-backed SaaS technology company based in Washington, DC. Our software solutions revolutionize how transportation and infrastructure systems—roads, rail, transit, bicycle, and pedestrian—operate. **What we build** - **Reduce traffic fatalities** - **Enhance pedestrian accessibility** - **Empower system operators to save time & money** You’ll work with talented engineers and data scientists applying emerging technologies, including **Artificial Intelligence** and **Machine Learning**, to build smarter tools for a diverse client base across the United States (with global ambitions ahead). --- ## Who You Are You’re a **product-minded software engineer** who turns customer problems into reliable, AI-enabled capabilities. You’ve built and shipped **production LLM features**, and you understand the difference between a convincing demo and a dependable product. You work across the stack—prototype quickly, validate both **value** and **correctness**, and turn experiments that work into production software. You know when **AI is the right approach** and when conventional software is better. You’re comfortable with ambiguous requirements and collaborate with engineering, data science, and customer-facing teams to identify where AI creates real value for transportation agencies. --- ## Expected Duties - Work with product, design, Customer Success, and data science to understand agency problems and validate where AI adds value (and where it doesn’t). - Design, build, and ship AI-enabled capabilities end to end—from data access to the application. - Integrate model-based features into existing software and data architecture without building unnecessary AI infrastructure; document key design decisions. - Design and maintain evaluations for AI features, including **correctness, grounding, authorization, appropriate abstention, and regression detection**. Define practical release criteria and use production feedback to improve quality. - Make AI-generated results traceable to underlying data, queries, and assumptions. - Enforce customer isolation and each user’s permissions, including when tools retrieve/query data; guard against **prompt injection**. - Own production features: **latency, cost, reliability, monitoring, failure modes, and incident response**. - Choose the right technique per problem (prompting, tool use, retrieval, text-to-SQL, fine-tuning, or no AI), balancing accuracy, cost, speed, and time to market. --- ## Required Skills & Experience - Bachelor’s degree in Computer Science, Data Science, or a related field - 5+ years building production software, including shipped LLM features used by…
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