About this role
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
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
Tech stack
LLM
About Infinity Constellation
Infinity Constellation is hiring for the ai engineer - everest role. NewJob aggregates active openings directly from Infinity Constellation's applicant tracking system, so this listing is current.
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