Principal Backend Engineer (Applied Ai)
- Compensation
- Not disclosed
- Location
- Mundelein, United States
- Work setup
- Hybrid
- Seniority
- Principal
- Employment
- Not specified
- Experience
- 8+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- 8+ years buildingbackend or distributed systems in production
- Proven ownership of services with real uptime, latency and scale requirements, with clear stories about what you built, the tradeoffs and what broke
- Experience designing and evolving APIs, services and event-driven systems
- Hands-on experience shipping LLM-powered or agentic features to real users, not just prototypes
- Strong in at least one backend language. Kotlin and Python are used today, but architecture judgment matters more than stack.
- Experience at a venture-backed startup or a company with a comparably high technical bar
- Comfort with ambiguity,strong communication, and opinions you’ll change when you hear a better argument
Nice to have
- Founding or earlyengineer experience
- Document processing, OCR or integrations with entrenched enterprise software
- Infrastructure ownership on AWS with infrastructure as code
- Background in civil, structural or MEP engineering, construction tech or CAD/BIM
Full description
Job DescriptionAbout the Company
\ NOur client is a venture-backed applied AI company rebuilding a $500 billion industry that has never had a real software platform underneath it: civil, structural and MEP engineering. Instead of selling software to engineering firms, they acquire them, keep their people and their names, and install their own technology and engineers inside. They are backed by a top-tier venture firm with significant capital set aside for acquisitions with this being highest-priority engineering hire in the company.
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About the Role
\ NThis is a hands-on Principal engineer seat: you’ll design and build the backend services and product features that bring AI into how engineering firms actually work. That means taking messy, real-world inputs like drawings, specifications, calculations and correspondence, and turning them into reliable production systems built on LLMs and agentic workflows. You’ll own systems from design through production, set the architecture the rest of the team builds on, and work directly with the CTO on technical direction. This is an individual contributor role for someone who still writes code every week.
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What You Will Do
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- Design, build andown backend services and APIs, from new product features to core platform services\ N
- Build production systems that use LLMs, agents and RAG to parse documents, automate workflows and act on unstructured data\ N
- Design agentic workflows that are reliable in production: evaluation, guardrails, retries, failure handling and human review\ N
- Lead the architecture of event-driven and asynchronous systems, including queues, background processing and integrations with legacy software\ N
- Shape multi-tenant architecture so each new firm is faster to onboard than the last\ N
- Own reliability for what you ship, including observability, incident response and performance\ N
- Use AI coding tools like Claude every day to move faster, and help set how the team uses them\ N
- Partner with the CTO and forward deployed engineers on long-term architecture and engineering standards\ N
What We Are Looking For
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- 8+ years buildingbackend or distributed systems in production\ N
- Proven ownership of services with real uptime, latency and scale requirements, with clear stories about what you built, the tradeoffs and what broke\ N
- Experience designing and evolving APIs, services and event-driven systems\ N
- Hands-on experience shipping LLM-powered or agentic features to real users, not just prototypes\ N
- Strong in at least one backend language. Kotlin and Python are used today, but architecture judgment matters more than stack.\ N