Senior Software Engineer, AI & Data

Renterra•Chicago, IL

8h•$150,000 - $200,000•Hybrid

About The Position

Renterra is a Series A–backed SaaS company modernizing the $100B+ heavy equipment rental industry. We’ve built an end-to-end platform that helps rental businesses run smarter, spanning operations, payments, marketing, accounting integrations, and more. Our platform contains a growing body of operational and financial data that can do more than power reports. We believe it can help rental businesses identify problems, make better decisions, and truly help them thrive! We’re looking for a senior engineer to build the data systems that make this possible, then use those systems to create AI agents and intelligent product experiences that solve real customer problems. This is a hybrid role based in Chicago, with regular in-office collaboration and flexibility for focused remote work.

Requirements

You’re an AI-forward builder who wants to own the full path from raw data to a customer-facing product that solves a real problem.
You’re a high-caliber software engineer at the Senior, Staff, or Principal level. You’ve built and operated production systems and bring strong product and architectural judgment.
You have deep experience with data architecture, SQL, and data modeling, including analytical databases such as ClickHouse. You understand how data structure and access patterns affect performance, maintainability, and cost.
You understand distributed and event-driven systems, including ordering, retries, deduplication, replay, schema evolution, and failure recovery.
You’ve shipped AI- or ML-powered product features and understand the full system around the model: data, retrieval, tool use, evaluation, observability, permissions, and fallbacks.

Nice To Haves

Building agentic systems that call tools or take actions in production
Retrieval, embeddings, semantic search, or hybrid search
Evaluation frameworks for AI agents and LLM-powered features
Classical machine learning, forecasting, anomaly detection, or optimization
Kafka, Redpanda, Flink, Spark, or similar event-processing systems
Change data capture and database replication
Data governance, permissions, privacy, and auditability
Financial, accounting, logistics, or other operational business data
Customer-facing analytics and reporting products

Responsibilities

Build our data and AI foundation: Design how operational and financial data is captured, structured, processed, stored, and queried across Renterra. This includes event architecture, data pipelines, and analytical systems such as ClickHouse.
Create AI-powered products: Build agents and intelligent workflows that use Renterra’s data to identify problems, answer questions, support decisions, and automate work for our customers.
Own production quality: Make data and AI systems reliable, observable, secure, and cost-effective. Design for failure recovery, data quality, permissions, model uncertainty, and appropriate human review.
Measure what works: Develop evaluations and feedback loops for accuracy, reliability, latency, cost, and customer impact. Use what you learn to improve both the underlying data systems and the product experience.
Work across the company: Partner with leadership, product, engineering, support, and customers to find valuable problems and turn them into shipped solutions.
Make pragmatic technical decisions: Choose the right approach for each problem, whether that is a deterministic workflow, analytical query, machine-learning model, LLM, vendor, or a combination of them.
Report directly to the CTO.