• Train, fine-tune, evaluate, and improve NLP, speech-to-text, and LLM-based models used in production environments • Work hands-on with chatbots, summarisation, and language understanding features, including retrieval-augmented generation (RAG) and vector-based retrieval systems • Design and run model evaluations, benchmarking existing approaches and validating improvements before deployment • Read, assess, and experiment with relevant AI/ML research and emerging techniques, translating promising ideas into practical, production-ready solutions • Contribute to prompt design, model optimisation, and iterative experimentation to improve accuracy, latency, and reliability of deployed models • Integrate models into existing backend services using Python-based APIs, collaborating closely with backend engineers • Ensure models are production-ready, maintainable, and resilient when deployed in live customer-facing systems • Support investigation and resolution of AI-related production issues in collaboration with engineering and platform teams • Work closely with engineering teams to align AI capabilities with product requirements and platform constraints • Communicate progress, trade-offs, and technical decisions clearly in planning and delivery discussions

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We're seeking a highly motivated and technically skilled AI Modeling Lead to join our Automation and AI team. This role requires strong machine learning and data science expertise, excellent coding practices, and the ability to translate real-world business challenges into impactful AI solutions. The ideal candidate is a hands-on contributor who thrives in a fast-paced, purpose-driven environment while operating within the core values and principles of the organization. - Lead the development and implementation of advanced machine learning models for strategic use cases. - Define modeling standards, validation strategies, and performance benchmarks. - Collaborate with business and technical teams to align models with operational goals. - Mentor and guide modeling team members, sharing best practices and driving technical growth. - Ensure model transparency, fairness, and governance compliance. Qualifications - Master's degree in computer science, Machine Learning, or a related field. - 7+ years of experience in AI/ML modeling. - Experience in technical leadership and/or cross-functional leadership. Requirements - Professional Degree (Ph.D) in Computer Science, Machine Learning, or a related field. - Industry knowledge/experience in finance or insurance. - Proven track record of delivering high-impact models to production. - Familiarity with responsible AI practices and regulatory considerations. - Expertise in predictive modeling, NLP, deep learning, and LLMs. Benefits - Work Solution: Hybrid (Tuesday-Thursday) or Remote (USA). - Relocation Eligibility: Available.

• Diseñar, desarrollar e implementar agentes conversacionales inteligentes utilizando Vertex AI Agent Builder. • Integrar LLMs de Google Cloud y de terceros en agentes conversacionales para mejorar la comprensión del lenguaje natural y la generación de respuestas. • Implementar técnicas de RAG para conectar agentes conversacionales con fuentes de datos externas y proporcionar respuestas precisas y contextualizadas. • Utilizar LangChain y LangGraph para construir flujos de conversación complejos y orquestar la interacción entre diferentes componentes de IA. • Optimizar el rendimiento y la escalabilidad de los agentes conversacionales en Google Cloud. • Aplicar las mejores prácticas de ingeniería de prompts para mejorar la calidad y la eficiencia de las interacciones con LLMs. • Colaborar con diseñadores de UX y otros ingenieros para crear experiencias de usuario atractivas e intuitivas. • Mantenerse al día con las últimas investigaciones y tendencias en IA generativa.

• Define and lead end-to-end AI architecture for complex ecosystems, balancing technical depth with business outcomes. • Translate business strategy into scalable AI technology solutions through discovery workshops, assessments, and roadmaps. • Act as a technical sponsor for CI&T’s most strategic accounts, working closely with C-level clients and non-technical stakeholders. • Lead architectural design, technology selection, and proofs of concept for critical AI platforms and innovation programs. • Govern technical quality across delivery squads, driving adherence to security, performance, scalability, and privacy standards. • Support pre-sales, proposal development, RFP responses, and technical visioning with account teams and clients. • Coach and mentor senior architects and technical leads, shaping technical career development paths.