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Salary: USD 250,000 - 300,000 / annual
Via Transportation is launching an incubator-style AI team operating like a startup within the company to expand beyond transit into adjacent markets. As a Staff AI Engineer, you'll be at the ground floor of this new initiative, building production-grade AI products end-to-end with real autonomy, direct leadership access, and the backing of a company already at scale.
You will own the full lifecycle of AI-powered solutions: problem framing, data pipeline design, deployment, and iteration in live environments. You'll work closely with city partners in a forward-deployed manner to understand problems deeply and iterate quickly on agentic solutions. You'll lead technical scoping workshops, directly interfacing with city leaders to solve challenging local problems using agentic workflows.
Your responsibilities include contributing to intelligent tooling involving data consolidation, predictive modeling, real-time decision-making, and LLM-powered experiences. You'll collaborate directly with product, data science, and operations teams to identify and prioritize high-impact AI opportunities across the business. You'll write clean, scalable backend code powering AI-driven features—designing APIs, managing data flows, and ensuring systems perform reliably at scale.
You'll help shape the technical culture of AI Labs from the ground up, contributing to how the team builds, reviews, ships, and iterates. You're expected to stay close to the frontier of AI development and proactively bring new ideas, tools, and approaches to the team.
REQUIREMENTS:
- 10+ years of hands-on experience building full-stack applications with a track record of owning features end-to-end (not isolated model or research work)
- 3+ years working with AI tools and/or building AI-powered products
- Deep expertise across the AI stack: LLMs, predictive modeling, and data infrastructure for real-world environments
- Strong core engineering skills: designing scalable APIs, working with distributed systems, writing clean and maintainable code
- Comfort with ambiguity and early-stage environments; ability to take ownership without explicit direction
- Strong cross-functional communication skills and intellectual curiosity to push AI boundaries
- Willingness to work directly with users and customers, including on-site collaboration and travel
