Design AI integration patterns and architecture standards across the SaaS platform
Integrate LLM APIs (OpenAI, Anthropic, AWS Bedrock) into production features
Build RAG systems, vector search, and embedding pipelines
Optimize latency, inference cost, and hallucination guardrails
Establish model evaluation, benchmarking, and observability processes
Define cost controls, usage monitoring, and security/PHI handling constraints
Evaluate use cases with Product for ROI and feasibility
Advise leadership on build vs. buy decisions for AI capabilities

Requirements

5+ years software engineering experience with strong Python backend skills
Production experience with LLM APIs, RAG systems, embeddings, and vector databases
Cloud-native architecture experience, preferably AWS
Experience in regulated or security-conscious environments
Product-minded systems thinker, comfortable with ambiguity and executive communication

Benefits

Remote first work environment
Health, Dental, Vision, Life and Disability Insurance options available day one.
401K - with match and immediately vested.
17 company holidays, 2 floating holidays plus competitive paid time off policy
Internal Advancement Opportunities

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonLLM APIsRAG systemsembedding pipelinesvector searchcloud-native architectureAWSmodel evaluationbenchmarkingobservability

Soft Skills

product-mindedsystems thinkercomfortable with ambiguityexecutive communication