Mechro Founding Applied AI Engineer

Gitwit•Tulsa, OK

38d•$165,000 - $190,000•Hybrid

About The Position

Mechro is seeking a Founding Applied AI Engineer to bring their AI troubleshooting platform to life. This role involves owning customer outcomes end-to-end, working directly with machinery manufacturers to transform real-world troubleshooting into an AI system. The engineer will be the technical partner responsible for the zero-to-one build, shaping the product with customers, and defining the intelligence layer for the heavy-equipment ecosystem. Mechro is an AI-native venture within Gitwit's venture studio, aiming to turn frontline troubleshooting into a continuous learning system. This position is for an engineer who wants to build a product that is actively used on job sites and in service bays by technicians diagnosing real machines.

Requirements

5+ years full-stack engineering experience with shipped, user-facing products.
Strong experience with React + TypeScript, Node/NestJS, and SQL/NoSQL databases.
Practical experience integrating LLMs/AI APIs into real applications.
Zero-to-one ownership stories demonstrating grit, ambiguity navigation, and user impact.
Experience running B2B/enterprise customer integrations.
Comfort balancing speed with reliability in early-stage systems.
Excellent written and verbal communication.
Strong "delivery energy". You like owning outcomes in the real world, not just writing elegant code.
Experience with RAG systems, vector databases, or ML evaluation pipelines.
Familiarity with SOC2-style security practices.
Prior startup or founding engineer experience.
Strong product sense and the ability to simplify complex workflows.

Nice To Haves

Founder-level equity
Relocation support
Excellent health, vision, and dental
401(k) with match
Generous PTO
Cell reimbursement, parking stipend
Weekly team lunches
Dog-friendly office
Flexible, high-autonomy culture

Responsibilities

Own the architecture and drive decisions about what gets built and why.
Lead full-stack development using React + TypeScript, Node/NestJS, and Postgres/MongoDB.
Build the AI layer, including LLM integrations, retrieval, embeddings, and evaluation loops.
Stabilize and scale the MVP into a production-ready troubleshooting assistant.
Run technical customer integrations, including scoping, implementation calls, and on-site visits.
Implement reliability systems: monitoring, alerting, runbooks, and incident response.
Establish early engineering culture, onboarding documentation, architecture patterns, and delivery cadence.
Translate user problems into product decisions that shape the roadmap.