Applied AI Engineer
RemoteUnited States
Job Summary
Design and deploy production-grade AI solutions using large language models, AI agents, and machine learning techniques to automate business processes across underwriting, operations, finance, and HR. Build intelligent workflows, scalable cloud-native services, and reusable components that integrate with enterprise platforms like policy administration and data repositories. Evaluate, fine-tune, and optimize foundation models while implementing guardrails, security controls, and monitoring frameworks to ensure accuracy and compliance. Collaborate with cross-functional teams to translate requirements into scalable AI applications, leveraging modern orchestration frameworks and vector databases. Support production systems through performance monitoring, troubleshooting, and continuous improvement. This role is fully remote within the US, requires US work authorization, and offers a competitive salary with comprehensive benefits including 401K, PTO, and parental leave.
Required Qualifications
- 3+ years of experience in software engineering, AI engineering, machine learning, or a related technical field, with at least 2 years designing and delivering production AI solutions
- Hands-on experience building enterprise applications using Large Language Models (LLMs), AI memory and context management, AI agents, prompt engineering, and orchestration frameworks
- Experience with deploying applied AI features and related cloud-native technologies
- Strong programming skills in Python or JavaScript, with experience developing RESTful APIs, microservices, and scalable distributed applications
- Experience integrating AI solutions with enterprise systems using REST APIs, event-driven architectures, vector databases, and knowledge repositories
- Familiarity with modern AI or orchestration frameworks
- Experience implementing AI evaluation, monitoring, observability, and testing frameworks to measure model quality, reliability, latency, and cost
- Understanding of Responsible AI principles, security, governance, prompt safety, model access controls, and enterprise AI compliance
- Experience with Git, GitLab/GitHub, CI/CD pipelines, Infrastructure as Code, and DevOps/MLOps practices for deploying AI applications
- Experience working with Databricks, SQL Server, or other enterprise data platforms
- Experience with modern cloud environments such as AWS, Azure, or Google Cloud Platform
- Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience
- Demonstrated ability to translate complex business problems into scalable, secure, and production-ready AI solutions while collaborating effectively with cross-functional teams
- You must live in the United States and be authorized to work in the United States without requirement of employment sponsorship/visa
Desired Qualifications
- Experience developing AI solutions for the property & casualty insurance industry, including underwriting, submissions, or policy administration
- Experience with Model Context Protocol (MCP), enterprise AI agents, multi-agent systems, vector databases, and modern AI engineering platforms
- Strong communication skills and ability to work cross-functionally with different departments
- Ability to travel up to 10% of the year
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