Sr AI ENGINEER - Software

The client is a technology organization operating at the scale of a major financial enterprise, building AI agents that serve millions of customers directly. This is not a chatbot bolt-on or an innovation-lab experiment: the client’s agentic platform sits in the production path of real customer conversations, with the reliability, latency, and safety bar that implies., Well established real estate company seeking and an experienced Leasing Manager to lead our growing talented team! This Jobot Job is hosted by: Josh Rabinowitz Are you a fit? Ea…

• 2 days ago

7+ years of software engineering experience, with senior/lead-level ownership of production systems. Proven hands-on delivery of LLM-based agentic systems in production not coursework, not POCs. The interview covers the architecture, failure modes, and eval strategy of a shipped system. Strong Python (primary agent/ML stack) and Java (service integration) both are daily-use languages here. Depth in the standard agent stack: LangChain, LangGraph, prompt/context engineering, tool/function calling, RAG pipelines. Working knowledge of PyTorch and model fundamentals enough to fine-tune, debug model behavior, and reason about tradeoffs. Experience with LLM serving/inference vLLM or comparable (TGI, TensorRT-LLM), plus commercial APIs (OpenAI, Anthropic, Bedrock/Vertex). Solid distributed-systems fundamentals: APIs, queues, caching, observability, CI/CD. Major Plus Hands-on experience with agent-builder platforms such as Sierra or Decagon deploying, extending, or evaluating them for customer-service use cases. Voice agents, real-time/streaming inference, or contact-center integration. Experience in regulated industries (finance, healthcare) model risk, compliance review, audit trails. Eval frameworks (LangSmith, Braintrust, custom harnesses) and LLM safety/guardrail tooling.