AI Engineer - Everest
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 132d ago
The date the source published, not the day we noticed it (2026-05-05). Last seen at its source 1h ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $160k–225k/yr
Middle 50% of 2161 listings that do state pay — Engineering · all levels · United States · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
ashby employer's own board first seen 11d ago · last seen 1h ago
The listing
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