AI Engineer - Everest

About Everest Everest is reshaping how elite executive assistance is delivered to founders, entrepreneurs, executives, and high-net-worth individuals. Our clients expect exceptional service: proactive, strategic, discreet, and seamless. We operate with the adaptability of a high-performing technology organization: iterating quickly, learning from feedback, and improving our systems at speed. We’re collaborative, supportive, and focused on sustainable excellence. Core Responsibilities - Design and implement backend systems that power agentic workflows across LLM, deterministic, and hybrid pipelines. - Own and evolve core infrastructure like context memory, orchestration layers, and prompt routing systems. - Design composable multimodal systems that dynamically execute workflows from unstructured inputs (text, audio, video, images). - Optimize latency, extensibility, reliability, and inference cost of multi-agent pipelines. - Collaborate with stakeholders to pressure-test workflows in the real world. - Help us make clear decisions about when to use LLMs vs. traditional systems—and how to do both well. - Develop and improve GraphRAG-based knowledge retrieval systems using Neo4j - Integrate and orchestrate LLM calls for document processing workflows What We're Looking For - 5+ years of experience in backend software engineering, preferably in Go or similar systems languages. - Shipped agentic LLM systems to production (not prototypes, not demos). - Built real-time systems, distributed async queues, or performance-critical services. - Deep understanding of prompt engineering, token budgeting, and context management. - Strong intuition for when to use AI—and when not to. - Thrive in small teams with high trust and high ownership. Bonus Points - Experience with RAG, embedding stores, and vector DBs. - Experience designing evals for AI agents and workflows - Familiarity with tool orchestration frameworks. - Understanding of the architectural tradeoffs of agentic systems, RAG, MCP, memory, and orchestrations. - Know how to work with (and around) the limitations of cutting-edge LLM technologies. - Background in AI safety, observability, or human-in-the-loop workflows. - Prefer building systems that are simple, scalable, and "good enough," without sacrificing maintainability or future flexibility. - Are fluent in small-team dynamics: high trust, low ego, shared accountability. Why Join Everest - Build the operating system for a category-defining company: Everest is redefining what tech-enabled executive assistance looks like—high-touch, high-taste, deeply strategic. You'll shape how we deliver that at scale. - Work with exceptional talent: Our team includes founders, senior engineers, and strong functional leads. - Founder-led, data-driven culture: We are builders who move fast, value judgment and systems thinking, and give real authority to people who earn it. Compensation & Benefits - Competitive salary - Meaningful equity - Medical, dental, vision healthcare benefits - Flexible PTO policy, 401k, disability insurance, etc. - Remote-first culture