СШАAI Agent Engineer
3 нед. назад
180k–225k USD / годСШАSenior
llmapache icebergtrino
Develop and improve AI agent systems for enterprise intelligence products.
О компании
- delivers enterprise intelligence at scale by giving organizations secure, governed access to all their data, wherever it lives. Built for distributed data environments, helps enterprises power AI and analytics without the cost and complexity of traditional data consolidation. With open standards including Trino and Apache Iceberg, enables trusted access to complete enterprise context while helping organizations avoid vendor lock-in. Leading global enterprises trust to fuel AI, analytics, and enterprise intelligence. Learn more at .ai .
Обязанности
- We build the AI layer for 's products, including AIDA. We design agents that let users ask questions in natural language and get accurate, grounded answers backed by their actual data. We operate with startup speed inside an enterprise company, shipping weekly and measuring results. This is the first dedicated agent engineering hire on the team.
- You will raise the bar on agent reliability, turning shipped features into systems users depend on. You will approach AI agents as production software systems, built with the same rigor as any large-scale backend platform. This is not a research role or a prototyping role. You will ship agentic features that work with messy real-world data, undocumented schemas, and diverse access patterns.
- You have already shipped agentic or LLM-powered systems at an AI startup or AI-focused product team. You bring proven patterns, knowledge of real failure modes, and operational lessons that would take the team months to learn through trial and error. You write code every day and ship every week.
Требования
- 5+ years building AI/ML systems, with at least 1 year shipping agentic or LLM-powered systems in production
- Direct experience at an AI startup or AI-focused product team (not consulting, integration, or agency work)
- Hands-on experience with agent frameworks (LangChain, LangGraph, CrewAI, Semantic Kernel, or custom)
- Production RAG pipeline experience (chunking strategies, vector databases, embedding models, reranking)
- Strong software engineering fundamentals: testing, observability, CI/CD, code review discipline
- Track record of shipping frequently and iterating on user feedback
- Ability to Travel : This role will require 25% in-person travel for purposes including but not limited to new hire onboarding, team and department offsites, customer engagements, and other company events. Actual travel expectations may vary by role and business needs.
Будет плюсом
- Experience with enterprise data systems (SQL engines, data catalogs, schema metadata)
- Experience building evaluation and observability pipelines for agentic systems
- Familiarity with JVM-based systems or polyglot development environments
- Contributions to open-source agent frameworks or tooling
- Experience with function calling, tool use patterns, and context window management
Условия
- is dedicated to maintaining fair and equitable compensation practices. The salary range provided for this role reflects the minimum and maximum targets for candidates across all U.S. locations and could be inclusive of variable compensation, such as commission or bonus. All employees receive equity packages (ISOs) and have access to a comprehensive benefits offering. Actual compensation packages are determined based on relevant skills, experience, education and training, and specific work location. For more information, connect with the recruiting team or Hiring Manager during the process as they can provide more detailed information about the salary range.
- Pay Range
- $180,000 — $225,000 USD
Другое
- Design and build agent architectures: tool orchestration, planning, memory, multi-step reasoning, error recovery
- Ship production-quality agent features with clear ownership from design through deployment
- Close the gap between demo and production: handle partial schemas, inconsistent metadata, mixed data formats, and unreliable source systems
- Introduce proven patterns for agent reliability: structured error handling, fallback chains, observability, guardrails
- Build evaluation suites that catch hallucinations, regressions, and grounding gaps before they reach users
- Collaborate with the AI Research Engineer to integrate grounding and retrieval into agent workflows
- Drive technical standards for agent development through code, not documents
- Turn improvements into measurable gains in task completion rate, accuracy, and time-to-value
- All-Stars have the opportunity and freedom to realize their true potential. By building alongside top talent, we’re empowered to take ownership of our careers and drive meaningful change. Anchored in industry-proven technology and unprecedented success, All-Stars are taking on the challenge everyday to disrupt our industry – and the future.
- Our global workforce is supported by a competitive Total Rewards program that reflects our commitment to a rewarding and supportive work environment. This includes a variety of benefits like competitive pay, attractive stock grants, flexible paid time off, and more.
- We are committed to fostering an intentional, inclusive, and diverse culture that drives deep engagement, authentic belonging, and an exceptional All-Star experience. We believe that diversity of thought, perspective, background and experience will enable us to own what we do, drive our success and empower our All-Stars to show up authentically.
- provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.