Backend/AI Engineer
- Salary
- $200K - $300K
- Level
- Mid
- Work type
- On-site · San Francisco
Not stated in the posting: visa.
Open. First seen 14 March 2026.
About the role
About Reducto
Reducto's standard text
Reducto is the agentic document platform for leading AI teams who demand enterprise performance at scale. We provide a comprehensive toolkit for working with documents the way a human would, combining custom in-house and leading frontier models to power efficient and accurate document workflows.
We’ve grown rapidly, increasing revenue 8x year over year and partnering with hundreds of companies, from leading AI teams like Harvey, Vanta, and Scale, to enterprise customers across FAANG and top trading firms.
Reducto has raised over $100M from world-class investors including a16z, Benchmark, and First Round Capital.
The Opportunity
As a Backend/AI Engineer, you'll work on our core API that powers document parsing for hundreds of companies. You'll integrate cutting-edge LLMs, optimize document processing pipelines, and build the infrastructure that makes state-of-the-art document understanding accessible at scale.
We would love to meet you if you:
- Philosophy: You are your own worst critic. You have a high bar for quality and don't rest until the job is done right—no settling for 90%. We want someone who ships fast, with high agency, and who doesn't just voice problems but actively jumps in to fix them.
- Experience: You have 2+ years of experience building real world applications and integrating LLMs into production systems
- Language: You're exceptional at Python
- Tools: Build your own tools as needed—like a quick Streamlit app to test hypotheses or create a dataset.
- Approach: A quantitative approach to building products. Ability to debug, experiment, and iterate fast. You should be comfortable getting hands-on with the full development lifecycle, from ideation to shipping to users.
The core work will include:
- Integrating and optimizing LLM calls for structured extraction, form filling, and document understanding tasks
- Making improvements to API design and pre-processing algorithms (chunking, structured extraction, etc.) based on customer feedback
- Building and improving document processing pipelines that handle everything from PDFs to spreadsheets at scale
- Experimenting with new techniques and output structures to improve LLM accuracy and reduce latency
- Building internal tooling and evals to better understand/analyze failure cases
- Working directly with the founders and customers to shape the product direction and engineering strategy
Bonus points if you:
- Have prior experience founding a company or building products at early stages
- Have experience with prompt engineering, fine-tuning, or building AI agents
- Are ambitious and driven, and care a lot about doing great work with great people
- Keep up with the latest developments in ML/AI
This is an in person role at our office in SF. We're an early stage company which means that the role requires working hard and moving quickly. Please only apply if that excites you.
About Reducto
Reducto's standard text
Nearly 80% of enterprise data is in unstructured formats like PDFs
PDFs are the status quo for enterprise knowledge in nearly every industry. Insurance claims, financial statements, invoices, and health records are all stored in a structure that’s simply impractical for use in digital workflows. This isn’t an inconvenience—it’s a critical bottleneck that leads to dozens of wasted hours every week.
Traditional approaches fail at reliably extracting information in complex PDFs
OCR and even more sophisticated ML approaches work for simple text documents but are unreliable for anything more complex. Text from different columns are jumbled together, figures are ignored, and tables are a nightmare to get right. Overcoming this usually requires a large engineering effort dedicated to building specialized pipelines for every document type you work with.
Reducto breaks document layouts into subsections and then contextually parses each depending on the type of content. This is made possible by a combination of vision models, LLMs, and a suite of heuristics we built over time. Put simply, we can help you:
- Accurately extract text and tables even with nonstandard layouts
- Automatically convert graphs to tabular data and summarize images in documents
- Extract important fields from complex forms with simple, natural language instructions
- Build powerful retrieval pipelines using Reducto’s document metadata
- Intelligently chunk information using the document’s layout data
Benefits at Reducto
Reducto's standard text
At Reducto, we’re invested in the well-being and growth of our team. Here’s what we currently offer:
- Unlimited PTO: We believe great work requires recharging.
- Lunch: Receive a free lunch to eat with your teammates daily at the office
- Reimbursed Transportation: Provide us with your receipts and we’ll take care of the costs
- Insurance: Generous health insurance covering medical, dental, and vision.
- Health and Wellness Budget: We provide up to $150/mo reimbursement for health and wellness spending, such as gym memberships, fitness classes, or similar.
- Parental Leave: Work with us to build a leave schedule that works for you and your family
Reducto is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law.
What this role asks for
Particular to this role
Prompt Engineering
Rare in Reducto's other 17 open postings.
Standard for data science / ML roles
Python
Common in data science / ML postings at any company.
In most of Reducto's ads
LLM
Named in most of its open postings, whatever the role.
62% of this description is written for the role. The rest is Reducto's standard text, folded away below.
Read against Reducto's other open postings on this site.
The team: Engineering HIRES STEADILY
This role is one of 12 open in Engineering. 2 were posted in the last 30 days and the oldest in November: a team that hires all year rather than one being built.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
LLM (10 of 12), Python (8 of 12), Kubernetes (4 of 12), JavaScript (2 of 12), Next.js (2 of 12), PostgreSQL (2 of 12), React (2 of 12)
OTHER ROLES ON THIS TEAM
- Software Engineer, Platform posted Oct 6
- Founding Data Engineer posted Oct 5
- Head of Product Engineering posted Sep 14
- Machine Learning Infrastructure Tech Lead posted Jul 16
- Founding Product Manager posted Jun 23
- Forward Deployed Engineer, Infrastructure Specialist posted May 28
- Machine Learning Infra Engineer posted May 13
- Lead Product Engineer posted Feb 3
- Machine Learning Engineer posted Nov 25
- Product Engineer posted Nov 25
- Forward Deployed Engineer posted Nov 25
From the team and dates on Reducto's own job board.
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