Senior Applied AI Software Engineer – US Hours

🕒 Setembro 21

🌐 Estados Unidos, Filipinas – Remoto

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⏰ Tempo Integral

🟠 Sênior

🧑‍💻 Engenheiro Full-stack

🦅 Patrocina Visto H1B

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👻 Score fantasma 25%

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🗣️🇺🇸🇬🇧 Inglês obrigatório

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M3 USA

201 - 500 funcionários

Fundada em 2000

🏥 Saúde

💼 Consultoria

⚕️ Seguro de Saúde

Healthcare • Consulting • Healthcare Insurance

A M3 USA é uma empresa especializada em fornecer soluções de pesquisa de mercado, recrutamento e promoção para a indústria de saúde. Seu foco é conectar profissionais de saúde, em especial médicos, a ferramentas e recursos que elevam a prática da medicina. Por meio de uma variedade de serviços, incluindo: • pesquisa de mercado qualitativa e quantitativa • promoção multicanal • recrutamento em saúde • ensaios clínicos a M3 USA apoia a indústria de ciências da vida, permitindo que profissionais de saúde se mantenham informados e ofereçam o melhor cuidado possível. Subsidiária da M3 Inc. , a M3 USA se relaciona com empresas farmacêuticas líderes e oferece extensas capacidades de pesquisa na Europa e nos EUA. A empresa é reconhecida por sua inteligência data-driven e por seus esforços na construção de redes dentro da comunidade de saúde.

Descrição

• Design, build, test and maintain production software systems • Develop scalable services, APIs, integrations and automation workflows • Contribute to architecture, engineering standards and best practices • Support deployment, monitoring and continuous improvement of production solutions • Design and deploy AI-enabled solutions using LLMs, agentic architectures and automation • Build production AI applications, copilots and workflow solutions • Develop prompt and context engineering frameworks • Implement RAG, tool-calling, memory and orchestration patterns • Evaluate and select appropriate AI models and technologies • Optimise latency, quality, reliability and cost • Monitor, test and continuously improve AI system performance • Operationalise statistical, predictive and AI models • Build validation, monitoring and feedback mechanisms • Contribute to digital twin and decision-support platforms • Translate business requirements into scalable technical solutions • Shape ideas into practical products and capabilities • Advise on feasibility, trade-offs and implementation approaches • Help define reusable AI platforms, patterns and capabilities across the organisation • Collaborate with Data Scientists, Engineers, IT teams and Business Analysts

🎯 Requisitos

• 5+ years of professional software engineering experience • Experience delivering production applications and services • Experience building AI-enabled products or intelligent systems • Experience across the full software development lifecycle • Strong React, Node.js and TypeScript as the primary development stack • Python for AI, automation and data-related workloads where appropriate • API development, systems integration and scalable architecture • SQL, data modelling and data integration • Automated testing, CI/CD and modern engineering practices • Practical experience with LLMs, generative AI and prompt engineering • Experience with RAG, agentic workflows and AI orchestration patterns • Foundation model evaluation, selection and optimisation • Monitoring, testing and support of AI systems in production • Must be willing to work in US Eastern time zone • CV must be submitted in English • Desirable: experience with Azure, AWS or Google Cloud • Desirable: vector databases and semantic search • Desirable: MCP connecting AI to enterprise tools and data • Desirable: MLOps and model lifecycle management • Desirable: AI evaluation/observability • Desirable: cloud-native deployment using Docker, Kubernetes, etc. • Desirable: digital twin, optimisation or decision science experience • Desirable: healthcare, data services or market research experience

🏖️ Benefícios

• Remote work arrangement • Opportunity to work with global healthcare and life sciences technology and research solutions • Work with modern AI technologies including LLMs, agentic AI and intelligent automation • Collaboration with Data Scientists, Engineers, IT teams and Business Analysts • Exposure to digital twin platforms, decision-support systems, AI-enabled research products and Copilot-style experiences

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