Sales Engineering
Technical proof behind the demo
I can run discovery, demo credibly, and answer technical objections because I have shipped the architecture behind the story.
Live Revenue Infrastructure · Aristova OS
Target reconnaissance matrix
Scale signal
Core tech stack
Primary buyer
Recent signal
Compiled from public sources before reaching out. Headcount appears only where the company publishes it. Where it does not, a citable scale or hiring signal is shown instead. Paid-enrichment estimates are excluded on purpose. A checked chip marks a technology I run in production.
Why this matters to your team
The same build maps onto four hiring problems.
Most candidates can sell, support, analyze, or build. The edge here is that the technical and commercial halves are connected by a production system I designed and operate.
Technical Account Management
Reliability from the build side
I understand retries, idempotency, external-provider failures, onboarding state, and customer-impacting reliability issues from production work.
Revenue Operations
Logic that protects the forecast
I built deterministic pricing, reconciliation logic, workflow automation, and data-integrity patterns that keep reporting accurate.
Customer and Partner Success
Repeatable execution
I turn operational chaos into repeatable workflows across customers, calendars, invoices, communication, and account state.
Aristova OS system map
One execution layer, end to end.
Typed web flows enter a transaction-safe data core, then reconcile payments, communication, finance, and AI-assisted intake back into an operator console with audit visibility.
transaction-safe core
product and provider boundary
human approval layer
The production stack
Every layer is something I have shipped and operate.
Not a tutorial stack. Each of these runs under real payment events, real customer state, and a test gate that has to stay green before anything ships.
Local DevOps & Reliability
Infrastructure parity: local containerized Postgres testing via Docker and WSL2. Type-safe schema generation and RLS boundary verification enforced in local sandboxes prior to edge deployment.
DockerWSL2Local PostgresSupabase CLIPowerShell
Infrastructure parity
Next.js 15 / React 19
App Router, server actions, and a typed request boundary so the front door of the system is type-safe end to end.
Frontend / EdgeSupabase Postgres RPC
Atomic multi-table writes and idempotent work claiming through PostgreSQL RPC so state stays correct under concurrency.
Transaction coreStripe + signed webhooks
SetupIntents, PaymentIntents, hosted invoices, and signature-verified webhooks that dedupe and reconcile money state.
Billing lifecycleIdempotent processing
A unit of work is claimed once across concurrent workers. No double-charge, no double-dispatch, recoverable on failure.
ReliabilityTwilio + Resend workflows
Retry-safe SMS and transactional email, sequenced through the same ledger so customer communication never fires twice.
Comms outboxAnthropic tool calling
Structured, schema-validated multi-turn intake where the model fills forms and the operator approves before anything commits.
AI layerArchitecture execution log
What the system does under load.
A representative trace of the operations Aristova OS runs on every job: signature verification, atomic writes, idempotent claiming, reconciliation. Illustrative, not a live feed.
Illustrative reconstruction of real operation types. No customer data, credentials, or live production traffic are shown.
Reliability patterns I built
The hard parts, handled under failure.
The difference between an automation demo and a production operating system is what happens when an event retries, a provider times out, or money state arrives out of order.
- Idempotent work claiming
A unit of work is claimed once across concurrent workers. No double-charge, no double-dispatch.
- Signed webhook verification
Provider events are verified before they touch internal state.
- Recoverable external operations
Provider calls assume failure and recover without corrupting customer state.
- Atomic multi-table writes
Customer, job, invoice, and ledger state commit through PostgreSQL RPC workflows.
- Deterministic pricing output
Same inputs, same defensible quote, every time.
- Provider event reconciliation
Late, repeated, or out-of-order events converge to one correct ledger.
- Manual operator approval
The system keeps humans in the loop where blind sending would create risk.
- Test-gated release discipline
The operational core is backed by 294 passing Vitest checks.
How I add value in the first 90 days
A plan that compounds.
Days 0 to 30
Map the terrain
- Learn the product, ICP, and buyer objections.
- Map CRM, demo, onboarding, renewal, and escalation loops.
- Identify where manual work creates risk or slows revenue.
Days 31 to 60
Assemble the assets
- Build a reusable technical objection library.
- Sharpen demo and discovery assets.
- Document repeatable handoff and customer workflows.
- Identify automation that reduces cycle time.
Days 61 to 90
Ship measurable wins
- Ship one GTM or customer-workflow improvement.
- Improve forecast, handoff, or implementation visibility.
- Create proof assets that help sales, success, and technical teams move faster.
Company-framed brief
Built for this operating problem.
This section appears when a company and role are passed into the architecture brief URL.
Role family
Systems
Why this matters here
The brief is framed around reliability, GTM workflow, and buyer trust.
Book time with AJ
Make scheduling easy.
Send two or three windows that work for you and I reply with a calendar invite. No form, no hidden workflow, just a clean handoff.
No contact address is published on this page. The button assembles a draft when you click it.
The operating layer I bring
If the role needs someone who can sell, explain, and improve the system behind the customer motion, this is the operating layer I bring.
AJ Jubara | Wesley Chapel / Tampa Bay | linkedin.com/in/abujbaraaj | Use "Open a message" above to reach me