Hire a Senior AI Engineer
10+ years of experience building production-grade AI systems, LLM applications, and full-stack platforms — remotely, worldwide.
Most recent: Senior Software Engineer at iDelsoft (Nov 2025–Aug 2026, ended) — available now, no exclusivity conflict. Full story →
Why Hire Diego Rodriguez for AI Development?
Ship Fast, Ship Right
Average 3-week delivery from kickoff to production. No scope creep — I define what we build upfront.
AI Specialization
Deep expertise in LLMs, RAG pipelines, AI agents, and ML systems — not just another generalist.
Remote & Async-First
Available globally. Clear communication, thorough documentation, and predictable delivery.
By the Numbers
What AI and Development Services Does Diego Rodriguez Offer?
LLM Application Development
End-to-end LLM apps: RAG pipelines with LangChain/LangGraph, vector databases, chatbots, document Q&A, and domain-specific retrieval systems.
Get a QuoteAI Agent Systems
Autonomous agents with tool/function calling, multi-agent orchestration, MCP integration, and business process automation.
Get a QuoteAI-Powered SaaS Platforms
Full-stack SaaS with LLM integration, subscription billing, admin panels, and AI-driven personalization at scale.
Get a QuoteML Risk Detection & Fraud Prevention
Real-time risk scoring, anomaly detection, and behavioral analysis pipelines using scikit-learn and feature engineering.
Get a QuoteFull-Stack Web Applications
React/Next.js frontends with Python/Node backends, PostgreSQL/MongoDB databases, REST or GraphQL APIs.
Get a QuoteAlgorithmic Trading Systems
Automated trading bots with reinforcement learning (PPO, SAC), real-time data pipelines, and portfolio dashboards.
Get a QuoteHow It Works
Discovery Call
We discuss your project, goals, timeline, and budget. I'll ask the right questions to scope the work accurately.
Build & Iterate
I deliver working increments with clear milestones. Regular check-ins keep you informed and in control.
Deploy & Hand Off
Production deployment with documentation, testing, and a handoff session so your team can maintain it independently.
Frequently Asked Questions About Hiring an AI Engineer
What is your typical project timeline?
Most projects ship in 2–4 weeks from kickoff to production deployment. A focused LLM application or RAG pipeline typically takes 2–3 weeks; a full AI-powered SaaS platform with billing and admin takes 6–10 weeks; ML risk detection systems or algorithmic trading bots range from 3–6 weeks depending on data availability and integration complexity. I define milestones and deliverables upfront at the start of every engagement, so you always know exactly what ships each week and there are no late surprises or scope creep.
How do you price projects?
I work on two models: fixed-price quotes for well-scoped projects, and monthly retainers (typically 20-40 hours/month, starting with a 1-month trial) for ongoing or exploratory work. Fixed-price projects include a detailed proposal breaking down every deliverable and cost before any work begins. For reference, per service: a production RAG pipeline $3,000–$6,000 (2–3 weeks); AI agent systems $5,000–$10,000 (3–5 weeks); a full AI SaaS platform $8,000–$15,000+ (6–10 weeks); ML risk/fraud scoring $4,000–$8,000 (3–5 weeks); trading systems $5,000–$10,000 (4–6 weeks); full-stack web apps $2,500–$6,000 (2–4 weeks). Retainer rates are available for teams that need continuous AI development, feature iteration, or maintenance. All pricing is discussed transparently on the discovery call — no hidden fees.
What tech stack do you use?
On the AI/ML side: Python with FastAPI, LangChain, LangGraph, scikit-learn, and PyTorch; vector databases including pgvector (PostgreSQL), Pinecone, and Chroma; all major LLM providers (OpenAI GPT-4o, Anthropic Claude, Google Gemini, and open-source models via Ollama). On the application side: TypeScript, React, Next.js, and Node.js for frontends and APIs; PostgreSQL, MongoDB, and Redis for data storage; AWS, Docker, Kubernetes, and Vercel for deployment. I choose the stack that best fits the project requirements — not the other way around.
Are you available for part-time / ongoing work?
Yes. Alongside project-based engagements, I accept monthly retainer arrangements for teams that need a dedicated AI engineer on an ongoing basis. A typical retainer covers 20–40 hours per month and can include continuous feature development, LLM fine-tuning and prompt iteration, monitoring and maintenance of deployed AI systems, or technical advisory for internal engineering teams. Retainers start with a one-month trial so both sides can assess fit before committing to a longer arrangement. Available to start immediately.
Do you sign NDAs and work on proprietary projects?
Absolutely. Confidentiality is the default — I never discuss, share, or reference client work publicly without explicit written permission. I am fully comfortable signing your company's standard NDA, IP assignment agreements, or any other confidentiality documentation before we begin discussions. I regularly work on proprietary AI systems, internal tooling, and competitive products where discretion is critical. If you have specific legal or compliance requirements (GDPR, HIPAA, SOC 2), let me know upfront and we can address them in the contract.
Is there a trial or pilot before committing?
Yes. Retainers start with a 1-month trial so both sides can assess fit. For project work, we can start with a small paid pilot — e.g. a retrieval prototype or an eval harness — before committing to the full build.
Who owns the code and IP?
You do. Full IP assignment on final payment is standard, and I sign your NDA and IP assignment agreements before we start. Everything built for you is yours, delivered with clean documentation and a handoff session.
What timezone do you work in, and is there overlap with the US or Europe?
I am based in Montevideo, Uruguay (UTC-3) — full overlap with US business hours (EST through PST) and morning overlap with Europe (CET). I work async-first with daily written updates, plus live calls in your overlap window.
What happens after launch? Is there maintenance?
Every build ships with docs, tests, and a handoff session so your team can maintain it. Post-launch, a monthly retainer covers monitoring, eval regressions, model and provider updates, and iteration. Bugs in delivered scope are fixed under a warranty window defined in the agreement.
Why hire Diego instead of an agency or talent platform?
Three differences: (1) AI specialization with production receipts — 94% fraud-detection precision, x402 agent payments, and an LLM fintech engine in production; (2) you work directly with the senior who ships, no hand-offs to juniors; (3) fixed scope with a $0 scope-creep guarantee and eval-gated delivery.
Ready to Start?
Let's build something remarkable together.