
Senior Applied AI Software Engineer β US Hours
Posted 6 days ago

Posted 6 days ago
This is a fully remote position, open to applicants in United States, +1 more country.
β’ Design, construct, test, and maintain production software systems.
β’ Develop scalable services, APIs, integrations, and automation workflows.
β’ Contribute to architecture, engineering standards, and best practices.
β’ Support the deployment, monitoring, and continuous improvement of production solutions.
β’ Design and implement AI-enabled solutions utilizing LLMs, agentic architectures, and automation.
β’ Create production AI applications, copilots, and workflow solutions.
β’ Develop frameworks for prompt and context engineering.
β’ Implement RAG, tool-calling, memory, and orchestration patterns.
β’ Evaluate and select suitable AI models and technologies.
β’ Optimize latency, quality, reliability, and cost.
β’ Monitor, test, and continuously enhance the performance of AI systems.
β’ Operationalize statistical, predictive, and AI models.
β’ Build mechanisms for validation, monitoring, and feedback.
β’ Contribute to digital twin and decision-support platforms.
β’ Translate business requirements into scalable technical solutions.
β’ Transform ideas into practical products and capabilities.
β’ Provide advice on feasibility, trade-offs, and implementation strategies.
β’ Help establish reusable AI platforms, patterns, and capabilities across the organization.
β’ Collaborate with Data Scientists, Engineers, IT teams, and Business Analysts.
β’ A minimum of 5 years of professional software engineering experience.
β’ Proven experience in delivering production applications and services.
β’ Experience in developing AI-enabled products or intelligent systems.
β’ Familiarity with the complete software development lifecycle.
β’ Strong expertise in React, Node.js, and TypeScript as the primary development stack.
β’ Proficiency in Python for AI, automation, and data-related tasks where applicable.
β’ Experience in API development, systems integration, and scalable architecture.
β’ Knowledge of SQL, data modeling, and data integration.
β’ Experience with automated testing, CI/CD, and modern engineering practices.
β’ Practical experience with LLMs, generative AI, and prompt engineering.
β’ Familiarity with RAG, agentic workflows, and AI orchestration patterns.
β’ Experience in foundation model evaluation, selection, and optimization.
β’ Experience in monitoring, testing, and supporting AI systems in production.
β’ Must be willing to work in the US Eastern time zone.
β’ CV must be submitted in English.
β’ Desirable: experience with Azure, AWS, or Google Cloud.
β’ Desirable: knowledge of vector databases and semantic search.
β’ Desirable: experience connecting AI to enterprise tools and data (MCP).
β’ Desirable: familiarity with MLOps and model lifecycle management.
β’ Desirable: experience in AI evaluation/observability.
β’ Desirable: experience with cloud-native deployment using Docker, Kubernetes, etc.
β’ Desirable: experience in digital twin, optimization, or decision science.
β’ Desirable: experience in healthcare, data services, or market research.
β’ Remote work arrangement.
β’ Opportunity to work with global healthcare and life sciences technology and research solutions.
β’ Engage with modern AI technologies including LLMs, agentic AI, and intelligent automation.
β’ Collaborate with Data Scientists, Engineers, IT teams, and Business Analysts.
β’ Gain exposure to digital twin platforms, decision-support systems, AI-enabled research products, and Copilot-style experiences.
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