Principal Software Engineer (AI Focus)

Assurant•Miami, FL

About The Position

Assurant is looking for a Principal Software Engineer with an AI focus to lead the design, development, and delivery of complex AI systems in production. In this role you will own the full lifecycle of AI-powered products — from architecture and model integration through evaluation, observability, and continuous improvement. You will serve as a technical leader across the organization, setting the standard for how we build reliable, scalable, and responsible AI systems.

Requirements

10+ years of professional software engineering experience with significant recent focus on AI systems, and at least 3 years operating at a staff or principal level.
Proven track record of driving complex AI systems from concept to production at scale.
Hands-on experience building production systems using AI orchestration frameworks such as Semantic Kernel, LangGraph, LangChain, or equivalent.
Deep understanding of AI evaluation methodologies — including offline benchmarks, online monitoring, A/B testing, and human evaluation — and experience building eval pipelines.
Strong expertise in LLM integration patterns including RAG, function calling, multi-agent architectures, and prompt engineering.
Proficiency in one or more modern programming languages (e.g., Java, Go, Python, TypeScript, C#).
Strong ability to communicate technical concepts to both technical and non-technical audiences.
Experience influencing engineering culture, standards, and best practices across an organization.

Nice To Haves

Experience in a fast-paced, high-growth environment.
Familiarity with modern cloud platforms (AWS, GCP, or Azure) and container orchestration (Kubernetes, Docker).
Background in CI/CD, observability, and reliability engineering practices tailored to AI workloads.
Demonstrated ability to deliver AI-first solutions using AI-assisted development tools such as Claude Code, Cursor, or equivalent.
Experience with model lifecycle management: selection, fine-tuning, versioning, deployment, and cost optimization.
Experience with vector databases, embedding models, and semantic search systems.
Knowledge of responsible AI practices including bias detection, safety testing, and content filtering.
Contributions to open-source AI projects or published technical writing on AI engineering topics.

Responsibilities

Architect and drive end-to-end delivery of production AI systems, including agentic workflows, retrieval-augmented generation (RAG), and model orchestration pipelines.
Define and implement robust evaluation frameworks — including offline evals, human-in-the-loop assessments, and automated regression testing — to ensure AI system quality and reliability.
Establish best practices for prompt engineering, model selection, fine-tuning, and guardrails across the organization.
Design and operate production infrastructure for AI systems, including monitoring, observability, cost management, and failure recovery.
Provide technical leadership across multiple teams, aligning AI engineering efforts with product and business strategy.
Evaluate and introduce new AI technologies, frameworks, and patterns to improve system capability and developer velocity.
Mentor and coach senior engineers, raising the organization's overall AI engineering maturity.
Lead design reviews, architecture reviews, and post-incident analyses for AI systems.
Partner closely with Product, Design, Data Science, and Infrastructure leadership to shape the AI roadmap and technical investment priorities.
Represent the engineering organization in cross-functional and executive-level discussions on AI strategy.