Founding Engineer - AI & Data Platform (Remote-Friendly)

Pear VC; New York (NY); Hybrid; USD 140,000 - 220,000; Full time

Benefits offered by this job

Competitive Compensation & Equity

Healthcare

Flexible Environment

Early Team Influence

Growth & Culture

Unlimited PTO

Job summary

A rapidly growing tech company in New York is seeking a Founding Engineer to shape the product and architecture. Join a passionate team and influence key decisions in building scalable APIs and AI-powered systems. Ideal candidates should have expertise in Python and SQL, with experience in data processing frameworks and a background in machine learning being a plus. The role offers competitive compensation, healthcare, and the potential for remote work while prioritizing in-person collaboration.

Qualifications

• 2+ years building scalable software systems.
• Expertise in Python and SQL.
• Comfortable with data processing frameworks like Airflow, Pandas, and Spark.
• Familiarity with infrastructure automation tools like Terraform and Docker.
• Background in LLM systems and Machine Learning is a big plus.

Responsibilities

• Architect scalable, high-performance APIs for financial data.
• Generate datasets using LLMs; apply evals and fine-tuning.
• Process large datasets using Airflow, Pandas, and Spark.
• Develop high-scale systems for web crawling.
• Manage infrastructure with Terraform, Docker, and AWS ECS.

Skills

Python

SQL

Data processing frameworks (Airflow, Pandas, Spark)

Infrastructure automation tools (Terraform, Docker)

LLM systems and Machine Learning

Job description

A rapidly growing tech company in New York is seeking a Founding Engineer to shape the product and architecture. Join a passionate team and influence key decisions in building scalable APIs and AI-powered systems. Ideal candidates should have expertise in Python and SQL, with experience in data processing frameworks and a background in machine learning being a plus. The role offers competitive compensation, healthcare, and the potential for remote work while prioritizing in-person collaboration.