This company builds a no‑code compliance automation platform, used by major financial institutions to streamline onboarding and manage risk. AI is the core engine, driving document review, network discovery, and risk assessment.
The role
You will join a lean engineering team focused on elevating the core AI layer from prototypes to production‑ready systems. Your work will involve designing and shipping RAG pipelines, vector search, and agentic workflows for compliance‑grade customers, owning the full lifecycle from design to operation on AWS and Kubernetes, and pushing the bar on evaluation, observability, and reliability.
The work
- Design, build, and iterate on production‑grade RAG pipelines, vector search, and agentic workflows.
- Ship AI systems that classify documents, surface critical signals, and automate actions within customer compliance flows.
- Own the operational excellence of your AI systems on AWS and Kubernetes, ensuring reliability and performance.
- Drive the evaluation, testing, and observability strategy for LLM‑powered systems in a high‑stakes environment.
What You Bring
- 2+ years of software engineering experience, with a proven track record of shipping AI features to production.
- Fluency in both TypeScript and Python; comfortable working across both languages.
- Hands‑on experience building with RAG, vector databases, and agentic patterns (e.g., LangChain).
- Experience operating production systems on AWS and Kubernetes, including deployment, monitoring, and debugging.
- A strong understanding of LLM evaluation, testing, and observability in production environments.
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