Staff AI Engineer

Responsibilities

• Write the code that matters most.
• Design and build production LLM and NLP systems, data pipelines and ML services. Guide critical core components through every stage, moving seamlessly from initial prototyping to production deployment and continuous oversight.
• Make the system trustworthy. Our users act on what GIA tells them.
• Build the evaluation, monitoring and traceability that catch failures like hallucinations, show why the system gave an answer, and keep a human in the loop where it matters.
• Set the technical direction. Define the architecture and engineering standards for our AI systems, and make the calls on models, build vs. buy, and the trade-offs between accuracy, cost and speed. Explain your reasoning clearly to engineers and leadership.
• Turn ambiguous problems into shippable solutions. Compliance and HR work rarely arrives as a clean spec. Work with product, customers and domain experts to decide what is worth solving with AI, frame it well and drive it through delivery.
• Raise the engineering bar.
• Lead design reviews and code reviews, write clear design docs, and mentor engineers at every level. Help shape how we hire, onboard and grow our AI engineers.
• Create reusable foundations.
• Build shared evaluation tooling, deployment pipelines and data practices so every project ships faster and more safely than the last.

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