Principal Software Engineer (AI Focus)

Job Summary

Assurant is seeking a Principal Software Engineer with an AI focus to lead the design, development, and delivery of complex AI systems in production. The successful candidate will own the full lifecycle of AI-powered products, from architecture and model integration to evaluation and continuous improvement. This role involves serving as a technical leader to set standards for reliable, scalable, and responsible AI systems across the organization.

Key Responsibilities

• AI System Architecture
• Drive end-to-end delivery of production AI systems, including agentic workflows, Retrieval-Augmented Generation (RAG), and model orchestration pipelines.
• Evaluation & Quality
• Define and implement robust evaluation frameworks (offline evals, human-in-the-loop, automated regression testing) to ensure system reliability.
• Best Practices
• Establish standards for prompt engineering, model selection, fine-tuning, and guardrails.
• Infrastructure
• Design and operate production infrastructure for monitoring, observability, cost management, and failure recovery.
• Leadership
• Provide technical leadership across teams, aligning AI engineering with product strategy; lead design reviews and post-incident analyses.
• Innovation
• Evaluate and introduce new AI technologies and frameworks to improve capability and developer velocity.
• Mentorship
• Mentor senior engineers to raise organizational AI engineering maturity.
• Collaboration
• Partner with Product, Design, Data Science, and Infrastructure leadership to shape the AI roadmap.

Required Qualifications

• Experience
• 10+ years of professional software engineering experience with significant recent focus on AI systems; at least 3 years at a Staff or Principal level.
• Track Record
• Proven history of driving complex AI systems from concept to production at scale.
• Frameworks
• Hands-on experience with AI orchestration frameworks (e.g., Semantic Kernel, LangGraph, LangChain, or equivalent).
• Evaluation
• Deep understanding of evaluation methodologies (offline benchmarks, online monitoring, A/B testing) and experience building eval pipelines.
• LLM Expertise
• Strong expertise in LLM integration patterns including RAG, function calling, multi-agent architectures, and prompt engineering.
• Programming
• Proficiency in modern languages such as Java, Go, Python, TypeScript, or C#.
• Communication
• Ability to communicate technical concepts to both technical and non-technical audiences.
• Cultural Influence
• Experience influencing engineering culture, standards, and best practices across an organization.

Preferred Skills & Experience

• Experience
• In fast-paced, high-growth environments.
• Familiarity
• With cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker).
• Background
• In CI/CD and reliability engineering tailored to AI workloads.
• Experience
• Delivering AI-first solutions using tools like Claude Code or Cursor.
• Experience
• With model lifecycle management (selection, fine-tuning, versioning, deployment).
• Knowledge
• Of vector databases, embedding models, and semantic search systems.
• Understanding
• Of responsible AI practices (bias detection, safety testing, content filtering).
• Contributions
• To open-source AI projects or published technical writing.

Job Details

Location: Remote (USA), Atlanta, GA
Job Type: remote
Posted: May 19, 2026