AI
American Family InsuranceDistinguished AI Architect
AI Architect developing data and AI architecture solutions for American Family Insurance. Leading integration design and participating in M&A discussions to achieve business outcomes.
About the role
- Design and build AI-powered services using LLMs, modern orchestration frameworks, and robust engineering practices
- Build scalable GenAI systems using transformer-based models and RAG architectures
- Design and implement AI pipelines including prompt chaining, embedding retrieval, and context management (MCP protocols)
- Engineer modular, well-tested Python code for AI agents, APIs, and microservices
- Use orchestration tools (LangChain, Semantic Kernel, n8n) to implement agent workflows and end-to-end AI experiences
- Collaborate with product and engineering teams to integrate AI into user-facing applications
- Partner with data engineering to build feature stores, vector search capabilities, and serve curated data
- Optimize AI systems for cost, latency, and scalability across Azure infrastructure (e.g., Azure ML, Azure AI Services)
- Lead on best practices around prompt evaluation, testing, model performance monitoring, and human-in-the-loop feedback
- Champion responsible AI design, including bias mitigation and data privacy safeguards
Requirements
- 7+ years of software or ML engineering experience, including 2+ years working on GenAI/LLM-based products
- Strong Python engineering skills (typing, testing, packaging, dependency management)
- Solid understanding of NLP/LLM fundamentals—tokenization, attention, transformers, embeddings, etc.
- Hands-on experience building with LLMs, prompt chaining, and retrieval-augmented generation (RAG)
- Familiarity with Model Context Protocol (MCP) standards: schema design, context injection, context window management
- Experience with orchestration and agentic frameworks (LangChain, Semantic Kernel, GPT agents)
- Experience working in CI/CD environments with ML Ops tooling (e.g., MLflow, AzureML, Kubeflow)
- Deep understanding of API design, microservices, and distributed system architecture
- Experience deploying scalable workloads on cloud platforms (Azure preferred) using Docker/Kubernetes
- (Nice-to-have) Experience with vector databases (e.g., Pinecone, FAISS, Weaviate)
- (Nice-to-have) Familiarity with serverless deployment patterns and infrastructure-as-code (e.g., Terraform, CDK)
- (Nice-to-have) Exposure to human-in-the-loop feedback systems and ethical AI design
- (Nice-to-have) Experience in AI governance, risk mitigation, and AI performance tuning
- (Nice-to-have) Consulting or client-facing delivery experience in data/AI-driven environments
Benefits
- 25 days off per year
- Closure between Christmas and New Year's
- Flexible remote work from abroad options for up to 6 weeks per year
- Learning & Development budget, including full access to Udemy courses
- Classpass membership
- Latest tech & tools, including home office budget and professional software subscriptions
- Equity share scheme to give long-term team members ownership in Riverflex
Job title
Job type
Experience level
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Degree requirement
No Education Requirement
Tech skills
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