Senior Development Engineer; AI​/ML Engineer Expertise

North Risk Partners is a fast-growing firm dedicated to serving the insurance and risk management needs of businesses and individuals. We provide expertise in Commercial Lines, Employee & Individual Benefits, Personal Lines, Surety, Claims, and Risk Management, and we have over 450 employees across more than 30 locations in Minnesota, Iowa, North Dakota, South Dakota, and Nebraska.

Job Type: Full‑time |
Location: Plymouth, MN (on‑site in Minnesota)

• Seniority level:
  Mid‑Senior level
• Employment type:
  
  Full‑time
• Job function:
  Engineering and Information Technology
• Industry: Insurance

This highly skilled Senior Development Engineer will design, build, and optimize systems that power analytics, AI Agentic workflows, and business intelligence solutions. Your work will combine enterprise system development, AI/ML development, and cloud technologies with hands‑on experience in AI and machine learning workflows. You will set technical direction for AI initiatives, influence cross‑functional stakeholders, and connect our strategic roadmap to measurable business impact.

• Design, develop, and maintain systems to support analytics, AI, and operational workflows
• Leverage best practices for AI/ML data modeling, storage, and retrieval across structured and unstructured data sources
• Optimize data workflows for AI/ML model training, inference, and deployment
• Collaborate with data engineers, developers, and business stakeholders to ensure scalable system availability and quality for AI initiatives
• Develop best practices in use of data infrastructure in cloud environments (e.g., AWS, Azure, GCP)
• Ensure compliance with data governance, security, and privacy standards
• Troubleshoot and resolve systems and AI pipeline issues promptly
• Support our AI strategy and roadmap aligned to business objectives and value creation
• Architect scalable, secure AI systems (ML pipelines, model serving, data ingestion, monitoring) leveraging cloud‑native services
• Conduct build‑vs‑buy assessments, vendor evaluations, and cost‑benefit analyses for AI tooling and platforms
• Establish model governance, risk controls, and ethical AI guidelines (bias monitoring, lineage, explainability, and human‑in‑the‑loop)

• Design, train, and deploy models (e.g., NLP, LLMs/RAG, computer vision, time‑series forecasting, recommendation systems)
• Optimize models for performance, latency, cost, and reliability, including prompt engineering and fine‑tuning for LLMs
• Integrate models into product and workflow experiences via APIs/microservices, event‑driven architectures, and secure data pipelines

• Partner across Product, Security, Legal, and HR to align delivery with compliance and change management
• Communicate complex technical topics to executive and non‑technical audiences; influence decisions with clarity and data
• Develop guardrails, templates, and playbooks that accelerate safe, responsible AI use across the organization

• Define KPIs & success metrics (e.g., model accuracy, adoption, cycle time, business impact, risk/incident rate)
• Oversee observability: data drift, model decay, cost tracking, usage analytics, and incident response processes
• Manage budgets, vendor relationships, and licensing for AI platforms and tools

• 7+ years in development engineering with 2‑4 years focused on AI/ML productization
• Expert in Python and core ML/AI libraries (e.g., PyTorch, Tensor Flow)
• Deep experience with LLMs (fine‑tuning, prompt engineering, RAG, vector databases such as FAISS/pgvector/Pinecone)
• Cloud proficiency:
  Azure (preferred), AWS, or GCP—covering model deployment, security, and cost optimization
• Proven leadership: leading teams/projects, mentoring, and influencing executive stakeholders
• Solid grasp of AI governance: responsible AI, security, privacy, compliance, and risk management
• Experience integrating AI into enterprise platforms (e.g., Microsoft 365, Dynamics, Power Platform, Azure OpenAI) is preferred
• Prior success delivering AI features at scale in production environments is preferred
• Strategic Thinking: connects…