EngineeringRemote

AI Engineer - Everest

Infinity · Remote

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Last seen by MeritLog September 9, 2026Source: AshbySource version: ashby-public-job-posting-v1

MeritLog read this listing from Infinity's Ashby job board and last checked it on September 9, 2026.

Source: the employer's Ashby job board. Open the original listing for current details.

Job details

Work model: Remote
Salary: Not listed by source
Location: United States
Company website: www.everestassistant.com

Hiring context

How this role compares at Infinity

Infinity has 20 live roles in MeritLog’s catalog across 5 job families, and 7 of them are in engineering. 5 of those listings publish a pay range, a disclosure rate of 25%.

Infinity concentrates this hiring in:

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

What the role asks for

What they're asking for

Experience with RAG, embedding stores, and vector DBs.SkillPreferred
Experience designing evals for AI agents and workflowsSkillPreferred
Familiarity with tool orchestration frameworks.SkillPreferred
Understanding of the architectural tradeoffs of agentic systems, RAG, MCP, memory, and orchestrations.SkillPreferred
Know how to work with (and around) the limitations of cutting-edge LLM technologies.SkillPreferred
Background in AI safety, observability, or human-in-the-loop workflows.SkillPreferred
Prefer building systems that are simple, scalable, and "good enough," without sacrificing maintainability or future flexibility.SkillPreferred
Are fluent in small-team dynamics: high trust, low ego, shared accountability.SkillPreferred

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

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

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