Summary
Next Insurance is dedicated to helping entrepreneurs thrive by providing innovative technology-led insurance solutions. The AI Engineer will design, build, and scale AI-driven capabilities, focusing on backend services and the integration of machine learning models into production systems.
Responsibilities
- Design, implement and optimize backend services that support AI workflows
- Integrate ML and LLM models into production systems with focus on performance, reliability and scalability
- Building and owning AI features end to end
- Evaluating/monitoring AI systems in pre-release/production environments
- Building reliable AI systems and writing production code
- Experience building or maintaining backend services or microservices
- Diagnose complex issues across data pipelines, model serving and backend components. This role focuses on building active APIs, microservices, and real-time serving infrastructure. It is not a Data Engineering role focused on ETL or batch processing pipelines
- Collaborate with product and cross functional teams to refine requirements and translate them into clear technical plans
- Contribute to system design, architecture reviews and code quality improvements
- Support innovation and continuous improvement by identifying opportunities and driving technical initiatives
Skills
- 2+ years of backend engineering experience in Python, Go, Java or similar
- Proven experience building high performance or distributed systems
- 2+ years of hands on experience integrating ML or LLM models into production
- Strong understanding of cloud infrastructure, microservices and observability
- Ability to operate effectively under ambiguity and navigate dynamic environments
- Strong communication and collaboration skills
- Familiarity with evaluating model performance using metrics such as precision, recall, F1 score, or other business-relevant measures is an advantage
Qualifications
Must Haves
- 2+ years of backend engineering experience in Python, Go, Java or similar
- Proven experience building high performance or distributed systems
- 2+ years of hands on experience integrating ML or LLM models into production
- Strong understanding of cloud infrastructure, microservices and observability
- Ability to operate effectively under ambiguity and navigate dynamic environments
- Strong communication and collaboration skills
Nice to Haves
- Familiarity with evaluating model performance using metrics such as precision, recall, F1 score, or other business-relevant measures is an advantage
Benefits
- Annual performance-based incentive program
- Partially subsidized medical plan
- Fully subsidized vision/dental options
- Life insurance
- Disability insurance
- 401(k)
- Flexible paid time off
- Parental leave
- Hybrid work model, requiring a minimum of three days per week on-site in the office, per company policy