Diego Rodriguez.
Why hire me

Senior Full-Stack & AI Engineer with production receipts.

10+ years shipping production-grade AI: LLM apps, RAG pipelines, agent systems, and ML risk detection. You talk to the senior who ships — fixed scope, eval-gated delivery, zero scope creep.

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Available now · Immediate start · Replies within 24h

Proof, not promises

94%

fraud-detection precision in production (high-traffic gaming platform)

x402

AI-native payment gateway processing autonomous agent transactions

iDelsoft

LLM proposal + recommendation engine in production for a US fintech SaaS

50+

production projects shipped across AI, SaaS, fintech, and trading

3-wk

average delivery for focused builds (RAG in 2–3 weeks)

Answers to the questions senior hires get vetted on

The short version — go deeper on the Hire page FAQ or the discovery call.

Evals before opinions

Every AI feature ships with an eval harness (DeepEval-style) that runs on every change and in CI. Retrieval precision, task success rate, and latency budgets are written into the proposal — regressions get caught before users see them.

Structured outputs, grounded answers

JSON schemas with Pydantic/Zod validation, retrieval grounding so answers cite sources, confidence thresholds with human-in-the-loop fallback, and prompt/output logging for audit. Reliability is engineered, not hoped for.

Cost and latency under control

Model routing (cheap models by default, frontier only where needed), prompt caching and compression, batched/async inference, and per-feature cost dashboards. Budgets are set before building, not discovered after.

A failure story, honestly told

Retrieval quality collapsed after an embedding-model swap — caught by evals, fixed by re-benchmarking chunking before touching prompts. Fraud-score drift under traffic spikes — fixed with behavioral feature re-engineering plus monitoring. Instrument first, fix systemically.

Diego vs. the alternatives

Why teams pick a specialized senior over a marketplace or an agency.

DiegoToptal / marketplacesAgency
Who ships your workDirect senior — the person on the call writes the codeVaries — generalist pool, screening overhead on youAccount-manager telephone game, juniors often do the work
Scope & pricingFixed scope, $0 scope-creep guaranteeHourly meter running, re-scoping is normalMarkup + change orders, budget drift
Delivery gatesEval-gated: acceptance thresholds in the proposal, evals in CIDepends on the individual you drawDemo-driven, rarely eval-backed
Timezone & communicationUTC-3: full US-hours overlap, async-first daily updatesOverlap varies by freelancerScheduled windows, slower feedback loops

Reference pricing

Final quote after a free discovery call. No hidden fees — scope frozen upfront.

Production RAG pipeline

$3–6K

Your docs become an assistant that cites sources. Chunking, embeddings, hybrid retrieval, re-ranking, evals. Ships in 2–3 weeks.

AI agent systems

$5–10K

Multi-step workflow automation with tool-calling agents, MCP integrations, eval-gated delivery, human-in-the-loop. Ships in 3–5 weeks.

AI SaaS platform

$8–15K+

Full-stack LLM product: auth, billing, admin, personalization. Production-hardened. Ships in 6–10 weeks.

ML risk & fraud scoring

$4–8K

Real-time scoring engines with behavioral analysis and monitoring — the same discipline as a 94%-precision production system. Ships in 3–5 weeks.

Trading systems

$5–10K

RL-based bots with real-time data pipelines, indicators, and portfolio dashboards. Ships in 4–6 weeks.

Full-stack web apps

$2.5–6K

React/Next.js frontends with Python/Node backends — tested, documented, deployed. Ships in 2–4 weeks.

Monthly retainer

20–40h/mo

Features, prompt iteration, monitoring, advisory. Starts with a 1-month trial.

Fixed-price = milestones (typically 30% kickoff). Retainers billed monthly in advance, USD via transfer or Stripe.

The capability catalog — 100 concrete deliverables

Beyond the 6 flagship services: everything below ships with fixed scope, evals where AI is involved, and docs. If it's software and it's not here, ask anyway.

LLM Apps & RAG10
Domain chatbot over your docs — Answers with citations, not hallucinations.
PDF / contract Q&A — Ask questions across thousands of pages.
Internal knowledge search — Semantic search over wiki, tickets, drives.
Support copilot — Drafts replies grounded in your help center.
RAG eval harness — Precision, recall and latency gates in CI.
Multilingual doc assistant — Query docs in EN, ES and PT.
Research summarizer — Digests papers, reports and filings.
Prompt-to-API migration — Replaces brittle prompts with structured outputs.
LLM cost optimizer — Routing plus caching cutting bills 40-70%.
Private / offline LLM setup — Self-hosted deployment, data never leaves.
AI Agents & Automation10
Lead qualification agent — Researches, scores and drafts outreach.
Invoice / AP automation — Extracts, validates and routes approvals.
Customer onboarding agent — Collects docs, verifies and provisions.
Report-generation agent — Weekly KPIs written straight from your DB.
QA / test agent — Auto-generates and runs regression suites.
Meeting-notes agent — Transcribes, summarizes and creates tasks.
Email triage agent — Classifies, drafts and escalates.
Data-entry agent — Forms, CRMs and spreadsheets on autopilot.
Competitor-watch agent — Tracks prices, launches and changelogs.
Human-in-the-loop workflow — Agents act, humans approve.
Chatbots & Assistants10
Website sales chatbot — Qualifies visitors 24/7.
WhatsApp business bot — Orders, FAQs and handoff to humans.
Slack / Teams assistant — Queries company data from chat.
Voice agent (phone) — Answers calls, books and routes.
Onboarding guide bot — Interactive product tours.
FAQ bot with escalation — Resolves the routine, routes the rest.
Multilingual support bot — EN, ES and PT from day one.
Appointment booking bot — Calendar sync, reminders, fewer no-shows.
Internal HR / IT bot — Policies, PTO and access requests.
Bot analytics dashboard — Containment rate, CSAT and fallbacks.
Data, ML & Analytics10
Fraud / risk scoring API — Real-time decisions under 100ms.
Churn prediction — Who leaves, why, and what saves them.
Demand forecasting — Inventory and staffing levels.
Anomaly detection — Alerts before dashboards turn red.
Recommendation engine — Products, content and upsells.
Sentiment analysis pipeline — Reviews, tickets and social.
Document classifier — Routes and extracts at scale.
Dashboard & KPI suite — Exec view over your warehouse.
ETL / data pipeline — Nightly jobs that never silently fail.
Model monitoring — Drift alerts plus retrain triggers.
APIs & Backend10
REST API design & build — Versioned, documented, rate-limited.
GraphQL layer — One endpoint over scattered services.
Auth system (JWT / OAuth / RBAC) — Login, roles and SSO.
Payment integration (Stripe) — Checkout, subscriptions, webhooks.
Webhook infrastructure — Retries, signing and replay.
Real-time WebSocket service — Chat, live odds, live tracking.
Multi-tenant SaaS backend — Isolation, billing and admin.
Microservice extraction — Breaks the monolith safely.
Third-party API integration — Any provider, resilient client.
API hardening audit — Security, limits, abuse prevention.
Frontend & Web Apps10
Marketing site (Next.js) — Sub-second loads, SEO-ready.
Admin dashboard — Tables, filters, roles, exports.
Customer portal — Invoices, tickets, usage, settings.
Booking / scheduling flow — Availability, payments, reminders.
Real-time dashboard — Websockets, charts, alerts.
Multi-step forms engine — Validation, save-resume, uploads.
Design-system implementation — Tokens, components, docs.
Legacy frontend migration — To React/Next with zero downtime.
Performance rescue — Core Web Vitals back to green.
Accessibility (a11y) pass — WCAG fixes that unblock deals.
E-commerce & SaaS10
Storefront (headless) — Fast catalog, checkout, search.
Subscription billing — Plans, trials, dunning, proration.
Marketplace MVP — Sellers, payouts, disputes flow.
SaaS onboarding funnel — Trial-to-paid instrumentation.
Pricing-page experiments — A/B tests that lift conversion.
Affiliate / referral system — Tracking, payouts, fraud checks.
Multi-currency checkout — FX, taxes, localized payments.
Order / inventory sync — Shopify, Woo or custom pipelines.
Churn-winback automation — Dunning plus offers that recover MRR.
Usage-based billing — Metered plans, invoicing, alerts.
Integrations & Migrations10
CRM integration (HubSpot / Salesforce) — Sync that stays synced.
Zapier / Make replacement — Native automation, no per-task fees.
Legacy DB migration — Zero-downtime Postgres moves.
Monolith to serverless — Lambda jobs for spiky workloads.
PHP / Laravel rescue & migrate — Stabilize first, modernize after.
Firebase to SQL migration — When you outgrow NoSQL bills.
SSO / SAML integration — Enterprise-ready login.
Data import / export center — CSV/Excel clients cannot break.
Email deliverability setup — SPF, DKIM, DMARC and templates.
Audit-log system — Who did what, provable.
DevOps & Cloud10
AWS architecture setup — VPC, IAM, least-privilege done right.
CI/CD pipeline — Tests, previews, one-click deploys.
Docker / Kubernetes rollout — Reproducible envs everywhere.
Cost-cut audit — Finds the 30-50% overpaid.
Uptime monitoring & alerts — On-call that sleeps at night.
Backup / disaster recovery — Tested restores, RPO/RTO defined.
Staging environments — Prod-like, seeded, disposable.
Log aggregation — One place to debug everything.
Secrets management — Rotation, no .env leaks.
Vercel / edge deployment — Global, cached, instant rollbacks.
Trading, Mobile & Emerging10
Trading bot (rules / ML) — Backtested before a dollar risks.
RL trading research rig — PPO/SAC experiments, logged.
Market scanner / alerts — Breakouts, funding, on-chain moves.
Portfolio dashboard — Positions, P&L, risk across venues.
Backtesting engine — Strategies vs years of data in minutes.
React Native app — iOS plus Android from one codebase.
Chrome extension — Sidebar tools, scrapers, autofill.
Web3 / DeFi integration — Wallets, swaps, on-chain reads.
Telegram / Discord bot — Alerts, commands, community tools.
AI image / document pipeline — OCR, extraction, generation.

Fixed quote within 24 hours of the brief. Most single deliverables land $500–$5,000 depending on scope.

Top hiring questions

Straight from the full hiring FAQ — 39 questions answered in English and Spanish.

How much does it cost to hire Diego Rodriguez?+
Two models: fixed-price quotes for well-scoped projects, and monthly retainers (typically 20-40h/month) for ongoing work. Reference ranges: a production RAG pipeline $3,000-$6,000; a full AI SaaS platform $8,000-$15,000+; ML risk or trading systems $4,000-$9,000 depending on data and integrations. Final quote after a free discovery call — no hidden fees, $0 scope-creep guarantee.
Is there a paid trial or pilot before committing?+
Yes. Retainers start with a 1-month trial so both sides assess fit. For project work, the discovery call produces a fixed-price proposal with milestones — you can also start with a small paid pilot (e.g. a retrieval prototype or eval harness) before the full build.
Can I see proof of production AI work, not demos?+
Yes: an ML fraud-detection system at 94% precision running in production for a high-traffic gaming platform; an AI-native payment gateway (x402 protocol) processing autonomous agent transactions; an LLM proposal-generation and recommendation engine in production for a US fintech SaaS (iDelsoft); plus RAG, eval, and trading case studies at https://www.diego-rodriguez.work/work and code at https://github.com/DiegoRodriguez93.
Why hire Diego instead of Toptal or an agency?+
Three differences: (1) AI specialization with production receipts (94% fraud precision, x402 agent payments, LLM fintech in production) — not a generalist pool; (2) you work directly with the senior who ships, no account-manager telephone game, at freelance rates below agency markup; (3) fixed scope with $0 scope-creep guarantee and eval-gated delivery.
How does he handle LLM hallucinations and reliability?+
With structured outputs (JSON schemas, Pydantic/Zod validation), retrieval grounding so answers cite sources, eval harnesses (DeepEval-style) that run on every change, confidence thresholds with human-in-the-loop fallback, and prompt/output logging for audit. Reliability is engineered, not hoped for.
How does he control LLM cost and latency at scale?+
Model routing (cheap models by default, frontier only where needed), prompt caching and compression, structured outputs to cut retries, batched/async inference, and per-feature cost dashboards. Cost and latency budgets are set before building, not discovered after.
Tell me about a production failure he diagnosed.+
Examples he discusses on calls: retrieval quality collapse after an embedding-model swap (caught by evals, fixed by re-benchmarking chunking before touching prompts), and fraud-score drift under traffic spikes (fixed with behavioral feature re-engineering plus monitoring). He instruments first (LangSmith/Datadog-style tracing, custom dashboards) and fixes systemically so it doesn't recur.
How do we start?+
Book a free 30-minute discovery call at https://www.diego-rodriguez.work/schedule, send the project brief via https://www.diego-rodriguez.work/hire or https://www.diego-rodriguez.work/contact, or email diegorodriguezpaiva1993@gmail.com — response within 24 hours.

Have more questions? The full FAQ covers payment terms, IP, NDA, compliance, and cancellation.

Read all 39 hiring Q&As →

Zero-risk terms, in writing

100% IP yours, day one

Full IP assignment on final payment; your NDA signed before substantive talks.

1-month retainer trial

Assess fit on real work. Walk away if it's not working.

Fixed scope, $0 scope creep

Deliverables and cost frozen upfront — re-scoping never lands on your invoice.

Pay per accepted milestone

Fixed-price work bills on shipped, accepted milestones — never on hours logged.

Let's scope your build .

Free 30-minute discovery call: goals, timeline, budget — then a fixed-price proposal with milestones. Response within 24 hours.

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