As a Senior Fullstack Engineer, you will play a key role in building and optimizing integrations that power scalable, high-performance data pipelines and intelligent systems. You’ll collaborate closely with a cross-functional team, to create seamless, efficient data flows that integrate with intelligent agents that perform key FP&A tasks.

Your expertise in data integration, API design, and working with LLMs will be vital in ensuring smooth interaction between systems, enabling advanced functionality that powers our product. You will bring a mix of data engineering experience and an understanding of LLMs to create systems that are both performant and adaptable to evolving business needs.

Key Responsibilities

Design, develop, and maintain robust data pipelines and integrations that connect various data sources and systems to ensure reliable and seamless data flow.
Build and optimize integrations with large language models (LLMs) and other machine learning and data science tools to enhance product capabilities.
Work with cross-functional teams, including data scientists, machine learning engineers, and product managers, to define technical requirements and implement end-to-end solutions.
Leverage tools such as Python, FastAPI, and databases (PostgreSQL, Redis) to build high-quality data integration systems that enable real-time processing and data accuracy.
Ensure smooth integration of third-party APIs, including LLMs (e.g., OpenAI), and other external data sources to extend the product’s functionality.
Develop, test, and maintain clean, maintainable, and efficient code, ensuring optimal performance in data pipelines and integrations.
Implement best practices for data governance, security, and scalability across the integration layer.
Mentor junior engineers, share knowledge of LLMs, and promote best practices in data integration across the engineering team.
Stay updated on emerging trends in data engineering, machine learning, and LLM technologies to ensure continuous product improvement.

Qualifications

Experience:

4+ years of professional software development experience, with a strong focus on data integrations and system architecture.
Proven experience with designing and implementing data pipelines, API integrations, and working with complex data systems.
Expertise in Python and backend technologies (e.g., FastAPI, Flask) to build efficient data systems and APIs.
Experience working with machine learning models, especially large language models (LLMs), and integrating them into production systems.
Familiarity with databases such as PostgreSQL and Redis, and proficiency in SQL for data manipulation.
Strong experience in version control with Git and containerization with Docker.
Experience with integrating third-party APIs and services, including LLM APIs (e.g., OpenAI, GPT models).
Familiarity with cloud platforms and services for data processing and storage (e.g., AWS, GCP).
Must have experience at an early-stage, venture-backed startup.
A background in fintech, finance or a related field is a plus.

Skills:

Strong problem-solving skills with the ability to design scalable and efficient systems for data integrations and LLMs.
Excellent communication skills, both written and verbal, with the ability to collaborate across diverse teams.
A proactive mindset with a passion for innovation and exploring new technologies in data engineering and machine learning.
Willingness to stay current with the latest advancements in data technologies, LLMs, and machine learning.

What We Offer