Senior Applied AI Software Engineer

Responsibilities

• ▹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
• ▹Optimize latency, quality, reliability, and cost
• ▹Monitor, test, and continuously improve AI system performance
• ▹Operationalize 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
• ▹Advise on feasibility, trade-offs, and implementation approaches
• ▹Help define how AI is applied across the organization through reusable platforms, patterns, and capabilities

Requirements

• ▹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 optimization
• ▹Monitoring, testing, and support of AI systems in production
• ▹Must be willing to work in the US Eastern time zone

Nice to have

• ▹Azure, AWS, or Google Cloud
• ▹Vector databases and semantic search
• ▹MCP: connecting AI to enterprise tools and data
• ▹MLOps and model lifecycle management
• ▹AI evaluation/observability: measuring and monitoring model performance in production
• ▹Cloud-native deployment: best practices for scalable, reliable AI applications (Docker, Kubernetes, etc.)
• ▹Digital twin, optimization, or decision science experience
• ▹Healthcare, data services, or market research experience

Soft skills

About the company

M3 is a Japanese global leader in providing groundbreaking, innovative technological and research solutions to the healthcare industry, with 5.8M+ physician members worldwide; M3 MR provides comprehensive healthcare market research recruitment, data collection, and insight support services across 70+ countries.