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# AI Engineer

- **Company:** Coterie Insurance
- **Location:** United States (Remote available)
- **Salary:** $115,000.0 - $145,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Microsoft Azure, Code Review, Continuous Integration, Python (Programming Language), Machine Learning, Natural Language Processing, Open Source Technology, Cloud Services, Standard Sql, Software Engineering, Systems Architecture, Software Organization, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Model Validation, Generative AI, Fastapi, Pytest, AI Platforms, Kubernetes, Information Technology, Data Analytics, Software Version Control, Docker, Databricks
- **Published:** July 18, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=24d15a2e39a59d2f

## About the Role

* Bachelor's degree or equivalent professional experience in Artificial Intelligence, Computer Science, Data Science, Economics, Engineering, Machine Learning, Mathematics, Operations Research, Statistics or a related quantitative field
 * Intellectual curiosity
 * Hands-on experience building machine learning or AI-powered applications
 * Hands-on experience working with large language models, prompt engineering, embeddings, vector databases, retrieval-augmented generation or agentic workflows
 * Strong Python proficiency including hands-on experience with Pytest, Pydantic and FastAPI
 * Strong software engineering and familiarity with production-grade development practices including documentation, testing, version control, code review, CI/CD and observability
 * Familiarity with tools/technologies such as AWS/Azure/GCP, Claude, Databricks, Docker, Gemini, Kubernetes, LangChain, LangGraph, OpenAI and SQL
 * Working knowledge of data privacy, security, access controls and responsible AI considerations
 * A bias toward practical, measurable outcomes and the ability to iterate quickly while maintaining high engineering standards, * Advanced degree or equivalent professional experience in Artificial Intelligence, Computer Science, Data Science, Economics, Engineering, Machine Learning, Mathematics, Operations Research, Statistics or a related quantitative field
 * Experience working in regulated industries such as banking, financial services, healthcare, insurance or related environments with meaningful audit, compliance, governance, and risk expectations
 * Experience building/leveraging reusable AI services or shared tooling that increases operational efficiencies
 * A clear point of view on the trade-offs between Anthropic, Google and OpenAI models across different task types
 * Hands-on experience acquiring data from the web at scale including scraping, proxy management and working with public APIs, aggregators and open-source datasets

## Description

The AI Engineer will work within the Research & Development (R&D) subdomain of Coterie's broader Data and Analytics (DnA) department to build, test and deploy intelligent systems that enhance business operations, customer and product capabilities. This role combines applied machine learning, software engineering and responsible AI practices to deliver reliable, scalable and secure AI-enabled solutions in production environments., * Partner with DnA teammates, software engineers and business stakeholders to deliver high-impact, AI-enabled solutions

 * Integrate AI capabilities into internal tools, customer-facing products and operational workflows using APIs, cloud services and modern software development practices
 * Implement secure and compliant AI systems that align with company policies, regulatory expectations and responsible AI principles
 * Productionalize AI and machine learning solutions including generative AI, natural language processing, predictive modeling and automation workflows
 * Evaluate model performance, reliability, safety, bias, latency, cost and business impact; help establish monitoring and feedback loops for continuous improvement
 * Assist with the documentation of technical decisions, system architectures and model assumptions
 * Stay current on emerging AI tools, frameworks, model capabilities and industry best practices; recommend and implement pragmatic adoption strategies


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