AI Engineer - Everest at Infinity (United States)
Infinity· United States·
Role details
Work type
Remote
Employment
Full-Time
Skills
Backend Software EngineeringGoAgentic LLM SystemsPrompt EngineeringToken BudgetingContext ManagementDistributed Async QueuesReal-time SystemsNeo4jRAGEmbedding StoresVector Databases
Benefits
Competitive Salary · Meaningful Equity · Medical, Dental, Vision Healthcare Benefits · Flexible PTO Policy · 401k · Disability Insurance · Remote-First Culture
Summary
Design and implement backend systems for agentic workflows, multimodal pipelines, and GraphRAG-based knowledge retrieval. The role involves optimizing infrastructure, optimizing latency, and collaborating with stakeholders to deploy production-grade AI solutions.
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
Why work at Infinity
- Culture highlights: The company explicitly defines its culture through a set of published principles: “Speed Over Perfection,” “Aggressive Yet Kind,” “Our Word Is Our Bond,” “Move Fast,” “Tell Us the Truth,” and “Figure It Out.” Emphasis on high standards, direct feedback, and extreme ownership without bureaucracy.
- Remote/hybrid/office policy: Mostly remote-first across the US (many jobs marked “Remote, USA”); physical HQ in New York, but employees work from home; some roles in Las Vegas
- Notable perks or engineering culture: Access to a shared brain across the portfolio — playbooks, customer intros, and lessons from every company; founders get back-office leverage so they focus on product and customers; engineering roles involve building AI-native products from scratch using cutting-edge applied AI
- Who thrives here: Self-starters who move fast, ship real products, iterate quickly, and want to be part of building category-defining businesses rather than maintaining existing ones
- Known downsides from culture page: High expectations — “We push hard. We have high standards.” — and a rejection of perfectionism: “Paralysis is worse than a wrong call you can reverse.”