Tradeweb Hiring! Full Time AI-ML Lead in - Ricebowl

We are seeking an experienced AI/LLM Engineer to design and build intelligent, language-driven agentic systems that translate user intent into structured execution workflows and. This role sits at the intersection of large language models, data science, and electronic trading, with a focus on building scalable, accurate, and explainable AI-powered decision systems.

Job Responsibilities

LLM Integration & Prompt Architecture

• Design and own the integration between conversational AI agents and external large language model APIs
• Develop and continuously refine prompt architectures that translate natural language into structured system actions and parameters
• Build confirmation and validation flows to ensure outputs are accurate, explainable, and auditable
• Establish and maintain high standards for interpretation accuracy at scale

Intent Parsing & Natural Language Processing

• Build systems that reliably map user instructions into structured parameters across varied phrasing, domains, and strategies
• Define evaluation frameworks to measure and improve NLP performance
• Handle ambiguity, edge cases, and fallback scenarios while maintaining user trust

Intelligent Recommendation Systems

• Design and develop engines that proactively recommend optimized configurations or actions based on historical behavior, real-time conditions, and benchmark data
• Incorporate multiple data sources to generate insights that outperform manual decision-making
• Continuously improve recommendation quality through feedback and iteration

Feedback Loops & Model Improvement

• Build mechanisms that leverage post-action or post-trade analytics to refine system recommendations over time
• Enable adaptive learning based on performance outcomes across different market or operational conditions

Benchmarking & Data-Driven Insights

• Collaborate with data and quantitative teams to develop anonymized benchmarking models
• Define statistical methodologies for performance comparison and optimization
• Ensure privacy, aggregation, and data governance standards are met
• Translate complex analytics into actionable outputs within AI-driven systems

Conversational Analytics

• Enable natural language interaction with complex datasets
• Build systems that interpret user queries, retrieve relevant data, and generate accurate, synthesized insights
• Support use cases such as performance analysis, comparisons, and trend identification through conversational interfaces

Chatbot deployment management

• Deliver product demonstrations to clients and internal teams
• Manage user access provisioning and provide technical onboarding support
• Advise clients on prompt engineering best practices to maximise platform value
• Gather, document, and prioritise client feedback to inform AI chatbot enhancements, including direct resolution of issues where possible

Qualifications

• 5+ years of experience in applied ML or AI engineering, with at least 2 years working directly with large language models in production
• Deep hands-on experience with LLM integration — prompt engineering, tool use, structured output, evaluation frameworks, and hallucination mitigation
• Strong Python — this is the primary development language for the agent layer and the SDK
• Experience building systems that translate unstructured natural language into structured, actionable outputs in a production environment
• Comfort working in a regulated industry where every model output needs to be explainable and auditable
• Ability to own a technical workstream end-to-end — architecture decisions, implementation, and quality bar