Hypertype is looking for an exceptional Founding Engineer to join a lean, ambitious team building AI infrastructure and applications for industrial companies.

This is a high-ownership startup role. You’ll work closely with the two founders, customers, and the business team to take products from idea → prototype → production → customer deployment. We’re looking for someone who is entrepreneurial, moves extremely fast, and is comfortable owning major technical decisions rather than waiting for detailed specifications.

We use AI-assisted development extensively to increase development speed, while maintaining high standards for reliability, security, architecture, and code quality.

What You’ll Own

• Build, ship, and maintain production systems across frontend, backend, AI, data, and cloud infrastructure.

• Develop web applications using React, Next.js, and TypeScript.

• Design backend services and APIs using Python and FastAPI.

• Build and improve end-to-end AI products, including RAG, AI agents, retrieval, evaluation, and data ingestion pipelines.

• Build data extraction pipelines capable of handling complex industrial documents containing text, tables, images, manuals, and other unstructured data.

• Work with Vector RAG, SQL-RAG, GraphRAG, embeddings, retrieval/reranking, prompt construction, and context management.

• Help operate our current GCP infrastructure and contribute to the migration of relevant infrastructure to Microsoft Azure.

• Prototype rapidly, test with customers, iterate based on real usage, and turn successful prototypes into scalable production systems.

• Work directly with customers to troubleshoot technical issues and ensure successful deployments.

• Define and track product and technical KPIs together with the founders and business team.

• Monitor production systems and continuously improve reliability, latency, AI quality, and infrastructure costs.

• Evaluate new AI models, frameworks, and infrastructure and make pragmatic build-vs-buy decisions.

What We're Looking For

Core Technical Experience

• Strong full-stack engineering experience with particular strength in backend engineering.

• 2-3+ years of Python experience, with a strong understanding of asynchronous programming, CPU-bound vs. I/O-bound workloads, multiprocessing, multithreading, GIL, asyncio, and production API development.

• Strong experience with FastAPI or similar Python backend frameworks.

• Production experience with TypeScript, React, and Next.js.

• Experience designing, deploying, and operating cloud-native applications on Azure, GCP, or equivalent infrastructure.

• Practical experience building end-to-end LLM/RAG applications, including:

  • LLMs and embedding models

  • Vector databases

  • Document ingestion, parsing, and chunking

  • Retrieval and reranking

  • Vector RAG / SQL-RAG / GraphRAG

  • Prompt and context management

  • Evaluation and monitoring

  • Latency and cost optimization

• Experience building agentic AI workflows, including tool use, orchestration, state management, and multi-step execution.

• Experience with complex data extraction and ingestion pipelines across text, tabular data, and images.

• Experience using AI coding tools extensively while still reviewing, validating, and taking full ownership of production code.

Startup Mindset

We are particularly interested in people who have previously been an AI startup founder, founding engineer, or early engineer at a pre-seed/seed-stage company.

You should:

• Be highly entrepreneurial and comfortable working with ambiguity.

• Enjoy building in a lean team alongside two founders.

• Have the hunger to go beyond a traditional 9-to-5 role when the company or customer requires it.

• Be able to move from prototype to production quickly without sacrificing engineering judgment.

• Be comfortable speaking directly with B2B customers and owning technical deployments.

• Understand how technology decisions affect unit economics, infrastructure costs, customer value, and company runway.

• Stay constantly up to date with developments across AI models, agents, developer tooling, and infrastructure.

• Be pragmatic: choose the simplest technology that solves the customer problem rather than over-engineering.

Strong Advantages

• 2+ years of GCP/Microsoft Azure experience, particularly migration experience.

• Experience with Firebase and BigQuery, particularly where these systems need to be migrated or replaced.

• Experience configuring or troubleshooting IPsec tunnels and enterprise networking.

• Experience operating LLM-powered applications at production scale.

• Experience with asynchronous processing, event-driven architectures, queues, caching, and background jobs.

• Experience systematically evaluating and improving AI quality and reliability.

• Experience building B2B software for customer support, aftersales, sales, industrial companies, or enterprise workflows.

• Experience with Rust (Tokio, Axum) or Go.

• Machine learning background.

• Experience at a startup that grew from pre-seed/seed toward Series A or beyond.

• Experience supporting fundraising from the technical side — creating technical materials, explaining architecture and AI differentiation, and presenting technology to investors.

Our Stack

Frontend
React · Next.js · TypeScript

Backend
Python · FastAPI

AI & Data
LLMs · AI Agents · RAG · Vector Search · SQL-RAG · GraphRAG · Document/Data Extraction

Cloud
GCP → Microsoft Azure
Firebase · BigQuery

Additional technologies
Rust · Go

Rust and Go currently represent a relatively small part of the stack, so deep expertise in both is not required.

The Person Who Will Thrive Here

You are someone who can look at a customer problem on Monday, build a working prototype quickly, put it in front of the customer, learn from real usage, and turn it into a reliable production product.

You don't think of yourself as only a frontend, backend, AI, or infrastructure engineer. You take ownership of the whole problem.

You care about the technology, but you also care about whether customers deploy it, whether it creates measurable value, whether the infrastructure economics make sense, and whether what you're building helps the company grow.

For the right person, this is an opportunity to have unusually high ownership over the technical direction and next stage of Hypertype.