AI Engineer

Stack

Kostenlos, nach der Anmeldung.

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Beschreibung

Recruiter for this role: Britney Dias Key Responsibilities · AI Feature Design & Delivery – Design, build and run AI powered features using large language models, translating product ideas into reliable, scalable production systems that deliver measurable impact. · LLM Integration & System Architecture – Integrate LLMs into existing applications and services, shaping backend architectures and APIs that balance performance, cost, security and maintainability. · Prompt Engineering & Model Optimisation – Develop, test and refine prompt strategies to improve model accuracy, safety, latency and cost efficiency across different use cases. · Hands-On Engineering – Build and maintain backend services and APIs using TypeScript and modern frameworks, contributing clean, well documented and maintainable code aligned with engineering best practice. · Cross-Functional Collaboration – Work closely with product, data and design partners to identify high value AI opportunities and shape solutions that are feasible, testable and aligned to user needs. · Evaluation & Monitoring – Define and implement evaluation approaches for LLM based systems, including logging, metrics and experimentation, to continuously improve quality and reliability in production. · Scalable AI Patterns – Contribute to shared approaches, architectural patterns and standards for building AI driven features across the platform. · Risk, Privacy & Cost Awareness – Make informed engineering decisions that consider data privac

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