採用
報酬
$160,000 - $300,000
福利厚生
•Unlimited Pto
•Healthcare
•401(k)
•Equity
•Meals
•Parental Leave
必須スキル
Python
Java
Go
Distributed Systems
System Design
About Hebbia
The AI platform for investors and bankers that generates alpha and drives upside.
Founded in 2020 by George Sivulka and backed by Peter Thiel and Andreessen Horowitz, Hebbia powers investment decisions for Black Rock, KKR, Carlyle, Centerview, and 40% of the world’s largest asset managers. Our flagship product, Matrix, delivers industry-leading accuracy, speed, and transparency in AI-driven analysis. It is trusted to help manage over $30 trillion in assets globally.
We deliver the intelligence that gives finance professionals a definitive edge. Our AI uncovers signals no human could see, surfaces hidden opportunities, and accelerates decisions with unmatched speed and conviction. We do not just streamline workflows. We transform how capital is deployed, how risk is managed, and how value is created across markets.
Hebbia is not a tool. Hebbia is the competitive advantage that drives performance, alpha, and market leadership.
The Team
The Document Intelligence team at Hebbia builds cutting-edge AI solutions that transform how users discover and interact with billions of private and public documents. Our products, including the Hebbia’s Browse application, enable intelligent document exploration, powerful search capabilities, and deep insights extraction. We focus on developing advanced data ingestion and search technologies that deliver intuitive, explainable, and highly responsive experiences. Working closely with customers, our team continuously iterates to address real-world challenges and drive impactful, data-driven decisions. Our goal is to empower users by seamlessly turning vast and complex document repositories into actionable intelligence.
The Role
Platform engineering at Hebbia is about excellent, scalable enablement. You are responsible for the core distributed systems that power billions of tokens across millions of dollars of AUM. You will be responsible for deploying efficient systems and building software tightly coupled with state of the art infrastructure/system design. Hebbia’s edge is built on operating on the edge of the tokenomics curve and you will serve as a key contributor in this area. We value engineers who think on their feet, innovate and can solve for exponential scale.
Responsibilities
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Own critical system components: Take complex requirements and turn them into robust, scaled solutions that solve real customer needs.
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Unlock O(1) universal indexing: Build and iterate on our high-scale document build system that enables constant time latency for indexing any content in the world, regardless of data volume.
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Drive performance optimization: Architect and implement performance-tuning solutions to ensure our systems operate efficiently at scale, minimizing latency and maximizing throughput across millions of documents.
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Mentor and guide: Provide technical leadership, mentorship, and guidance to junior engineers, fostering a culture of learning and growth.
Who You Are
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Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field. A strong academic background with coursework in data structures, algorithms, and software development is preferred.
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5+ years software development experience at a venture-backed startup or top technology firm, with a focus on distributed systems and platform engineering.
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Proficiency in building backend and distributed systems using technologies such as Python, Java, or Go.
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Deep understanding of scalable system design, performance optimization, and resilience engineering.
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Extensive experience with cloud platforms (e.g., AWS)
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Working experience with one or more of the following: Kafka, Elastic Search, PostgreSQL, and/or Redis
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Knowledge of workflow orchestration and execution platforms like Airflow, Temporal or Prefect.
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Proven experience enabling observability patterns.
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Ability to analyze complex problems, propose innovative solutions, and effectively communicate technical concepts to both technical and non-technical stakeholders.
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Proven experience in leading software development projects and collaborating with cross-functional teams. Strong interpersonal and communication skills to foster a collaborative and inclusive work environment.
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Enthusiasm for continuous learning and professional growth. A passion for exploring new technologies, frameworks, and software development methodologies.
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Autonomous and excited about taking ownership over major initiatives
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Bonuses:
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Experience building distributed systems leveraging technologies such as etcd or Apache Zookeeper.
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Frequent user of AI products, especially during the development lifecycle (i.e. Cursor, Claude Code, etc).
Compensation
The salary range for this role is $160,000 to $300,000. This range may be inclusive of several career levels at Hebbia and will be narrowed during the interview process based on the candidate’s experience and qualifications. Adjustments outside of this range may be considered for candidates whose qualifications significantly differ from those outlined in the job description.
Life @ Hebbia
PTO: Unlimited
Insurance: Medical + Dental + Vision + 401K
Eats: Catered lunch daily + doordash dinner credit if you ever need to stay late
Parental leave policy: 3 months non-birthing parent, 4 months for birthing parent
Fertility benefits: $15k lifetime benefit
New hire equity grant: competitive equity package with unmatched upside potential
総閲覧数
0
応募クリック数
0
模擬応募者数
0
スクラップ
0
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Hebbiaについ て

Hebbia
Series BHebbia is an American technology company that develops artificial intelligence and automation tools for financial and legal research. The company was founded in 2020 by George Sivulka, a former Stanford University PhD student, with its headquarters in New York City.
51-200
従業員数
New York
本社所在地
$1.3B
企業価値
レビュー
4.0
10件のレビュー
ワークライフバランス
3.2
報酬
3.8
企業文化
4.1
キャリア
4.2
経営陣
3.5
75%
友人に勧める
良い点
Flexible work hours and remote options
Great team culture and supportive environment
Good benefits and perks
改善点
Heavy workload and overwhelming demands
Long hours during peak projects
Compensation could be better
給与レンジ
12件のデータ
Junior/L3
Junior/L3 · Analyst
1件のレポート
$156,000
年収総額
基本給
$120,000
ストック
-
ボーナス
-
$156,000
$156,000
面接体験
62件の面接
難易度
3.4
/ 5
期間
14-28週間
内定率
37%
体験
ポジティブ 66%
普通 20%
ネガティブ 14%
面接プロセス
1
Phone Screen
2
Technical Interview
3
System Design
4
Behavioral
5
Team Fit
よくある質問
Tell me about a challenging project
System design question
Coding problem
Why this company
ニュース&話題
Show HN: An unstructured data workspace for data transformations with LLM
hi HN!<p>a couple of months ago I had to analyze a few thousand audio recordings to help identify issues with customer support. i was able to get some raw high-level initial results with python scripts invoking LLM APIs, but they were too general and unhelpful. writing basic prompts is easy, but tuning them and making them specific enough to ensure no faint signal is missed is hard. you need to iterate through the data with an initial prompt, segment the data into different buckets, chain anothe
HN
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3w ago
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4
Official Reddit Home of Hebbia | A New Era of Institutional Intelligence
Founded in 2020 by George Sivulka, Hebbia was purpose-built to meet the demands of finance. Today, Hebbia is the leading AI platform for institutional finance—backed by Andreessen Horowitz, Peter Thiel, and Index Ventures. We are trusted by investment banks and over 40% of the largest asset managers by AUM trust Hebbia to work the way they do: fast, accurate, and collaborative across the full deal cycle. We have joined Reddit to connect with the financial professionals who use Hebbia to move f
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3w ago
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1
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1
Seyfarth Leads Next Phase of Deal Execution and Diligence Through AI Partnership with Hebbia - Business Wire
Business Wire
News
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5w ago
Neuromorphic sphere topology Hebbian learning as a path to grounded intelligence
I've been working on a hypothesis and want to get feedback from people who know more than I do. The hypothesis Intelligence might be a phase transition at scale, not an algorithmic problem. Fly: 100k neurons — no generalization Mouse: 70M — basic associative learning Human: 86B — abstract reasoning This doesn't look like a smooth curve. It looks like thresholds. If that's true, then no amount of architectural cleverness crosses it — only scale + grounding does. The grounding probl
HN
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5w ago
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