AI Engineer — Aircraft Data

AIP Holding, Inc.; Northern (KY); Hybrid; USD 83,000 - 165,000; Part time

Benefits offered by this job

Paid trial task

Remote work

Weekly invoicing

Flexible hours

Contract through Deel

Job summary

AIP Holding, Inc. is building a transaction and ownership intelligence platform for business aviation. We seek a builder who can turn messy aviation data into a structured, trustworthy product used in live deals.

You will own data ingestion pipelines, valuation logic, and ML-enabled features, working with a small team including a fractional CTO. This is a remote, hourly contract via Deel with flexible hours and a paid trial task.

Qualifications

• You must understand aircraft systems, airframe terminology, and aviation regs (AD/SB knowledge helpful).
• Pilot licence (PPL+) or equivalent aviation education/experience is required or highly valued.
• Operational aviation time (MRO, CAMO, avionics, flight ops, OEM) is preferred.

Responsibilities

• Ingest and extract data from registries, scanned logbooks, maintenance records, and flight data to feed the platform.
• Develop and maintain performance and comparison logic on top of the ingestion layer.
• Build LLM-in-the-loop systems with auditable accuracy and traceability.
• Evaluate models to detect when outputs are wrong before customers see them.
• Deliver user-facing features that expose structured aviation data and insights.

Skills

Pilot licence (PPL+)

Aviation domain knowledge

Hands-on aviation ops experience

Education

Degree in aeronautical or aerospace engineering

Job description

Remote Contract via Deel, hourly, invoiced weekly Must partially overlap US hours

We're building the transaction and ownership intelligence layer for business aviation — the system of record for what an aircraft is, who owns it, what it's worth, and what happened to it.

Currently in stealth. In closed beta with a small group of brokers and principals who use the product on live deals and tell us to our faces when it's wrong.

Two founders. One with 27 years in tech, media and SaaS, and multiple exits. One with 30 years in business aviation. You'll work directly with both, plus a fractional CTO (PhD, ML).

Your mission

Turn the ugliest data in aviation into a product people pay for.

Aircraft data is scattered, contradictory, half-scanned, and older than most of the people reading this. Registries disagree with logbooks. Logbooks disagree with each other. Serial numbers get transposed. Airframes change registration three times and countries twice.

Your job: make it structured, trustworthy, and queryable — fast.

Use whatever works:

• LLM extraction pipelines
• OCR on 1970s carbon-copy maintenance entries
• Entity resolution across registries
• Scrapers
• Embeddings and retrieval
• Valuation and performance models
• Agents that do the boring parts
• Something nobody's tried

If it works, we double down. If it doesn't, we kill it that week.

We want a builder, not a researcher. We're not writing papers. We're shipping into live transactions where a wrong ownership record kills the deal and the customer relationship with it.

Non-negotiable: you know aircraft

This is aviation software. You cannot write it without understanding the aircraft.

Every panel we ship encodes a technical judgement. A payload-range comparison is not a lookup of two published figures — it's a tradeoff under fuel reserves, ISA deviation, cruise setting and runway performance. A valuation is not a regression on hours — it's engine programme status, damage history, AD and SB position, avionics currency. An engineer who doesn't understand what the numbers mean will build something that computes cleanly and is wrong at the design level. That is not caught by testing, and it is not caught by us reviewing the PR.

You need at least one of:

• A pilot licence — PPL or above, any authority
• A degree in aeronautical or aerospace engineering
• Real operational time inside aviation: MRO, CAMO, avionics, flight ops, flight test, or an OEM

And you need to talk about an airframe without a glossary. TBO. AD compliance. SB status. Damage history. Total time vs. TSO. Part-ML vs. Part 91. Payload-range tradeoff. What "engine on programme" does to a valuation. The difference between an AFM and an AMM — and why only one of them can be quoted to a buyer.

No aviation background → not a fit.

What you'll own

• The ingestion and extraction pipelines that feed the platform — registry data, scanned logbooks, maintenance records, flight data
• The performance and comparison logic that sits on top of it
• LLM-in-the-loop systems where accuracy is auditable, not vibes
• Evaluation: knowing the model is wrong before the customer does
• User-facing features off the back of it, not just backend plumbing

You'll own this layer end to end. You won't own the whole architecture — the surfaces, the warehouse and the product direction sit with the technical co-founder, and there's a fractional CTO on call for the ML questions. What you get is the hardest, least-solved part of the system and the authority to decide how it gets built.

Who you are

• You've shipped production software with AI in it — not a demo, not a notebook
• You treat LLMs as unreliable components you engineer around, not as magic
• You'd rather ship one thing that's right on Friday than five that are nearly right in October. You cut scope, not corners
• You treat traceability as part of the build, not overhead added afterwards — every output can be traced to a source, and you can say how confident the system is in it
• You're comfortable being the only engineer in the room on your part of the system
• You like data that fights back
• You read AFMs for fun and you're only slightly embarrassed about it

Bonus

• You own or share an aircraft
• You've built something on ADS-B, registry, or fleet data
• You've worked on performance, valuation, pricing, or marketplace models
• Type rating, IR, or mid-training
• Reading German or French (EASA-side registry and TCDS material)
• Side projects with users

Shape of the engagement

• Contract through Deel, hourly, invoiced weekly, paid on time
• Full-time or part-time both work. If you're a final-year aero student who ships, two focused days a week on defined workstreams is a real option — say so in your application
• Paid trial task first: half a day at your hourly rate, on real (anonymised) data, before any longer engagement
• Mutual NDA before the trial, since it touches customer records
• Start: as soon as the trial clears

Why take it

• The problem is genuinely unsolved. Nobody has built trustworthy structured ownership and maintenance history at scale in this market. The incumbents sell lists; we're building the record
• A co-founder who has sold aircraft for three decades answering your domain questions in real time. That input is not available anywhere else
• Paid properly from day one. Hourly, contracted, invoiced weekly, paid on time. No unpaid founder energy, no deferred anything
• Real flexibility on hours, structured around defined workstreams rather than presence