Three ways to work together.
I work with teams building AI-integrated software for government and enterprise operations — back-office platforms, internal tools, mission-critical systems. Three formats depending on where your product is: from auditing what isn't landing, to designing and building from scratch, to ongoing ownership as fractional.
AI Audit
USD 1,500 · 2 to 3 weeks
For teams who already have AI in production and don't understand why users aren't using it, don't trust it, or why something doesn't quite click in the experience.
A focused audit of the AI layer in your software: how it's implemented, how it integrates with the rest of the system, how it's presented to the user, where trust breaks. An audit that connects each architecture decision with how AI actually reaches the user in production — because in AI systems, that boundary doesn't exist.
It's the lowest-risk way to start working together. Most engagements start here and grow from there, once we both see how the work fits.
You get a prioritized findings report, a live walkthrough, and a working prototype where it makes sense — built on the actual model, not a static mockup.
Ideal when you've already shipped and usage isn't taking off.
Learn more about AI Audit →AI Application Build
Let's talk · 6 to 12 weeks depending on scope
For teams building software with integrated AI — whether a new application, a redesign of an existing one, or evolving an internal operational system into AI-native architecture — and want it designed for real usage from the start, not patched after launch.
I design and build the complete system end-to-end: use cases and acceptance criteria, interaction patterns, technical architecture (retrieval, context design, guardrails, evaluation framework), and full-stack implementation that goes to production.
This isn't a deck of recommendations. You get a working system, documented architecture decisions, and code your team can maintain and extend.
It works equally well for new applications (designed before code is written), redesigns of features that didn't land, or the evolution of internal operational systems into AI-native architecture.
Pricing defined per case based on complexity and depth.
Ideal when you have a specific build you want to get right the first time.
Let's design it →Fractional AI Engineer
Let's talk · 3-month minimum, then month-to-month
For teams continuously building with AI who need senior judgment inside the team — someone with end-to-end ownership of the AI work, from architecture to delivery, so your team can focus on the rest of the product.
I work alongside your product and engineering team as an embedded engineer: I lead the design and construction of AI features, review designs and implementations before they ship, define the standards of trust and real-world usage, and maintain coherence across features as the product grows. Not a consultant waiting on tickets — an owner who takes the AI work off your plate.
You get sustained architectural direction without the cost of a full-time hire. Minimum 3 months to do real work, then month-to-month with no lock-in.
Pricing defined per engagement based on team size, scope, and time commitment.
Ideal when AI is core to your roadmap and you don't have someone senior inside the team owning the AI work.
Let's talk →Need something more specific?
For one-off features, fixes, specific integrations, or work that doesn't fit the three formats above — let's talk. Custom engagement, scoped tightly, defined in a first call.
Tell me what you need →How engagements typically grow
Most teams start with an audit. It's the lowest-risk way to see how I work and to identify what's actually broken. From there, the path becomes clear:
→ Some teams need a specific build. We move to AI Application Build.
→ Some realize they need ongoing senior judgment. We move to Fractional AI Engineer.
→ Some need both — a build now, ongoing partnership after. We do both, sequentially or in parallel.
You don't commit to anything beyond the audit when we start. We define the next step together based on what we find.
What I don't do
Clear boundaries are part of working well together.
I don't train or fine-tune models. That's ML engineering, a different specialty.
I don't sell prompts, libraries, or packaged tools.
I don't do isolated UI design without system context.
I don't replace engineering teams or act as a development vendor.
I don't add AI just because it's trendy. Sometimes the answer is not using AI at all.
Not sure which one fits your case?
Tell me where your product is. The first conversation is free.
Schedule a call →