# Staff Innovation Engineer, Marketplace

**Company:** [Built](https://hotfix.jobs/companies/built)
**Location:** Nashville, TN
**Role:** Fullstack Engineering
**Experience:** 7+ years
**Skills:** Microservices, Distributed Systems, APIs, Temporal, aws textract, google cloud document ai, Claude, gemini, OpenAI, RAG, llm evaluation, document processing, Machine Learning, Data Engineering
**Posted:** 2026-08-07

> Builds durable marketplace systems and rapidly validates customer-facing products, including AI-powered workflows for unstructured documents. The role requires 7+ years of software engineering experience, strong distributed-systems fundamentals, and hands-on experience shipping full-stack products with LLMs and document-extraction tools.

## Job Description

## Responsibilities

- Design and build durable, reusable Marketplace services and primitives, including purchase orders, contract terms, invoicing rails, and workflow/status state machines.
- Use fine-grained microservices and asynchronous workflow orchestration such as Temporal.
- Partner directly with customers to scope problems and ship working versions of new marketplace products, then iterate based on customer feedback.
- Optimize launched products, workflows, click paths, quality, craftsmanship, adoption, and usage.
- Build and refine agent harnesses and layered prompting systems to automate workflows involving unstructured documents.
- Use AWS Textract, Google Cloud Document AI, Claude, Gemini, and OpenAI based on document needs and cost profiles.
- Build and use evaluation tooling to test and improve AI systems before and after production deployment.
- Partner with product, design, sales, and the General Manager on customer problems, pricing, go-to-market input, and product decisions.
- Mentor engineers through code review and pairing.
- Contribute to system design and architecture decisions.
- Maintain service and product API boundaries as the team scales.

## Requirements

- 7+ years of software engineering experience.
- Strong backend and distributed-systems fundamentals, including designing reliable and maintainable services and APIs.
- Experience building and shipping 0-to-1 products or features in fast-iteration environments with real customers.
- Experience integrating multiple LLM providers, such as Claude, Gemini, and OpenAI.
- Experience with document-extraction tooling such as AWS Textract and Google Cloud Document AI.
- Experience building agent harnesses, RAG pipelines, or other AI/LLM-integrated workflows.
- Experience with evaluation or testing practices for AI/LLM systems.
- Comfort working across the stack in a full-stack-capable engineering role.
- Curiosity about customer problems, low ego, and a preference for close collaboration with product.

## Nice-to-haves

- Data engineering, machine learning, or heavy document-processing experience.
- Experience in financial services, construction, real estate, payments, lending, insurance, or other complex B2B environments.

## Compensation and benefits

- No compensation or benefits details were provided in the posting.

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