Senior Software Engineer, Data Systems & AI

August 9

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Scrunch AI

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Artificial Intelligence • Marketing • SaaS

Scrunch AI is a technology company that focuses on optimizing brand visibility in the age of artificial intelligence. Their Agent Experience Platform provides insights on how AI interprets brands, enabling businesses to adapt their marketing strategies for a landscape where AI increasingly influences customer decisions. Trusted by over 500 prominent brands, Scrunch AI helps clients monitor their competitive positioning and uncover actionable insights to enhance their presence and effectiveness in AI-driven environments.

11 - 50 employees

Founded 2023

🤖 Artificial Intelligence

☁️ SaaS

📋 Description

• The Scrunch product involves acquiring and processing a lot of data, both using LLMs and more traditional analytics methods. • In this role you will play a huge part in successfully delivering our roadmap and ultimately in giving our customers the tools they need to succeed in the AI era. • Because we are a small organization, this is a full stack role. • While most of your work will be focused on building features related to our data pipelines, usage of LLMs, analytics APIs, etc., you'll need to do whatever is necessary to deliver value to our customers. • This can include some light React work but also work creating notifications, alert emails, scheduled reports, connectors into third party systems, etc.

🎯 Requirements

• Have extensive experience building & using web APIs, including handling authentication, authorization, caching, rate limiting, etc. • Experience building API for external customers is a big plus. • Experience with relational (transactional) databases, particularly PostgreSQL. • Experience with analytics tools and technologies, such as: • Analytical SQL, maybe with a modern analytical data platform like Snowflake, Google BigQuery, DuckDB, Spark SQL, etc. • Experience with analytics packages like Pandas or Polars is a plus. • Experience with streaming analytics is a plus. • Experience writing batch and streaming/interactive data processing pipelines. This could mean any of: • Big data tools like Flink, Beam (GCP Dataflow), Spark, etc. • Job queues and task processing frameworks (Celery, Resque, or cloud-based options like Google Cloud Tasks) • Multi-step durable execution frameworks like Temporal or Inngest • In-house or home-rolled versions of any of the above you've used at previous companies. • The ability to quickly understand source data and validate output data quality • Experience using LLMs and/or traditional ML techniques to build classifiers, data extractors, summarizers, etc. • Not required but a big plus: experience building evals for LLM-based tools to assess and improve accuracy at these kinds of tasks