Principal Engineer - AI Engineering/AI Software Engineering/Applied AI
Core
Design, build, and maintain production-grade AI-powered applications and agentic systems for fraud investigation, decision automation, and process optimization.
Role type
Principal Engineer, Applied AI
Builds
Production AI systems, agents, RAG pipelines, and LLM-powered workflows integrated into analytics and decision management platforms.
Domain
Financial analytics, fraud detection, decision automation, applied AI
Deliverable
production ML models | product features
Required skills
Python, TypeScript, LLM SDKs (Anthropic, OpenAI, Google), agent frameworks (LangChain, LlamaIndex, LangGraph), RAG architectures, vector stores (Pinecone, Weaviate, pgvector), evaluation pipelines, model fine-tuning/distillation, orchestration, tool use, guardrails, observability, inference optimization.
Preferred skills
Embeddings, information retrieval, offline/online evaluation metrics, A/B testing, open-source contributions.
Technologies
Python, TypeScript, LangChain, LlamaIndex, LangGraph, Anthropic SDK, OpenAI SDK, Google SDK, Pinecone, Weaviate, pgvector, MCP.
Responsibilities
Design and build production AI systems including agents and RAG pipelines; translate product requirements into technical designs balancing latency and cost; develop evaluation frameworks for LLM features; drive end-to-end delivery of AI features including prompt engineering and tool design; build and operate the application layer around foundation models; optimize inference performance and cost across the serving stack.
Seniority
Principal, hands-on IC with mentorship
