Applied Research Engineer, Agents

About Hebbia

Hebbia is an AI platform for investors and bankers, generating alpha and driving upside. Founded in 2020 and backed by Peter Thiel and Andreessen Horowitz, Hebbia powers investment decisions for major financial institutions including BlackRock, KKR, Carlyle, Centerview, and 40% of the world’s largest asset managers. Our flagship product, Matrix, provides industry-leading accuracy, speed, and transparency in AI-driven analysis, trusted to help manage over $30 trillion in assets globally. We deliver intelligence that gives finance professionals a definitive edge by uncovering signals, surfacing hidden opportunities, and accelerating decisions with unmatched speed and conviction. Hebbia transforms how capital is deployed, risk is managed, and value is created across markets.

The Team

The Agents team at Hebbia is responsible for building core document understanding capabilities, co-piloting experiences for Matrix, and deep, multi-source research functionalities. We have developed our own agentic frameworks powered by distributed systems built for scale, focusing on steerable, reliable, and explainable agentic systems that can handle vast amounts of customer data. Our goal is to create an indispensable and delightful product that unlocks unknown insights for customers worldwide, moving fast and building first-of-their-kind systems.

What we’ve built:

• A custom multi-agent framework powering deep research capabilities and co-piloting interfaces, paired with distributed systems infrastructure for long-running agentic tasks.
• The world’s most powerful and scalable LLM inference engine – a distributed, asynchronous DAG orchestrator capable of incorporating live graph mutations, cooperating in tandem with our LLM throughput management capabilities.
• Elastically scaling data representation and metadata generation, powering the most effective private data retrieval systems.
• Industry-leading agents solving problems from buy-side company diligence to multi-billion dollar M&A.

The Role

As an Applied Research Engineer, you will serve as the crucial link between research, industry, and application, significantly influencing the future of our core natural language processing systems. You will be instrumental in enabling agentic capabilities across the Hebbia product suite, owning experiments and Proof of Concepts (POCs) that combine the latest research findings with high-value problems faced by our customers daily. Leveraging our deep relationships with foundation model providers, you will partner to beta test models, experiment with new features, and develop guidance on relative model strengths.

This role demands prior expertise in NLP, machine learning systems, and LLM evaluation; experience building with foundation models and working with Attention-based NLP models is a strong plus. It is ideally suited for an individual who excels at both running experiments with novel LLM techniques and building production-grade, LLM-enabled software systems, embedding directly within the software development lifecycle.

Responsibilities

• Focused on LLMs, you will play a crucial role in analyzing and interpreting complex data types to derive and implement cutting-edge insight generation systems.
• Iterate and explore new LLM and NLP techniques, maintaining our foothold as an industry leader.
• Utilize your expertise in statistics, programming, and machine learning to develop and deploy data-driven models and algorithms.
• Contribute to solving business problems, improving processes, and enhancing overall company performance.
• Collaborate with cross-functional teams to improve NLP/LLM capabilities in the application.
• Stay up-to-date with the latest advancements and research in the space.
• Collaborate with software engineers to integrate agentic capabilities into existing systems or develop new applications.
• Ensure that systems are efficient, maintainable, and well monitored.
• Iterate on validation and testing frameworks.

Who You Are

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Master’s degree in Computer Science, Mathematics, Machine Learning, or a related field is a plus.
• 7+ years of software development experience at a venture-backed startup or top technology firm, with a focus on applied machine learning systems.
• Strong programming skills in Python.
• Experience with NLP and text processing libraries such as NLTK, SpaCy, or Apache Tika.
• Experience with Search and Indexing technologies.
• Proficient in machine learning techniques and algorithms.
• Experience working with foundational models and corresponding APIs.
• Knowledge of statistical analysis and data scraping techniques.
• Prior experience in developing NLP models and systems.
• Experience with prompting and building LLM applications and agents is a plus.
• Excellent problem-solving and analytical skills.
• Strong communication and teamwork abilities.
• Strong capability to translate research into production software systems.

Bonuses:

• Experience building agentic systems or LLM enabled products.
• Frequent user of AI products, especially during the development lifecycle (i.e., Cursor, Claude Code, etc.).