Hire LLM Engineers — AI Specialists for Your Team
LLM engineers from Latin America who build RAG systems, fine-tune models, and ship AI features to production with LangChain and vector databases. US time zones, at ~50% below US rates.
Start Hiring — FreeWhat does a LLM Engineer do?
An LLM engineer builds production applications powered by large language models. They architect retrieval-augmented generation pipelines, design and version prompts, wire models into agents that call tools, and ship features like chat assistants, summarization, and extraction. Their day-to-day blends API integration, context engineering, evaluation harnesses, and the latency, cost, and reliability tradeoffs of running models in production.
Unlike a traditional ML engineer who collects datasets and trains models from scratch, an LLM engineer is applied and product-focused: they treat foundation models as a given and extract value through prompting, retrieval, fine-tuning, and rigorous evaluation. The hard problems shift from gradient descent and feature engineering to grounding, hallucination control, token cost, prompt regression, and orchestrating multi-step agentic workflows reliably.
AILUM places nearshore LLM engineers from Latin America who have already shipped real GenAI features to production. They work US time zones, integrate directly into your team, and cost roughly half of US equivalents, with month-to-month engagements and no recruiting fees.
LLM Engineer skills & technologies you can hire
The core language for LLM work, used to build pipelines, agents, evaluation harnesses, and async services that orchestrate model calls at scale.
Framework for chaining prompts, tools, memory, and retrievers into agents; also fluent in LlamaIndex and LangGraph for orchestration.
Hands-on with chat completions, function/tool calling, structured outputs, embeddings, and streaming, plus Anthropic and open-weight model APIs.
Designs retrieval-augmented generation: chunking, embedding, hybrid search, reranking, and grounding answers in source documents to reduce hallucination.
Works with Pinecone, Weaviate, pgvector, and Qdrant for semantic search, indexing strategy, metadata filtering, and similarity tuning.
Applies LoRA/QLoRA and supervised fine-tuning, plus dataset curation and eval, when prompting and retrieval alone fall short.
How much does it cost to hire llm engineers in Latin America vs the US?
A US-based LLM engineer typically costs $160k-$220k in base salary, and far more once benefits, payroll taxes, and recruiting fees are added. AILUM's nearshore LLM engineers in Latin America range roughly $50k-$85k all-in. The gap reflects regional cost of living, not skill, and there are no recruiting fees or long-term commitments.
Get an exact quote for your role →What do llm engineers build?
RAG chatbots that answer questions over internal docs, wikis, and support tickets, with citations back to the source passages to keep answers grounded.
AI agents that plan multi-step tasks and call tools or APIs, such as automating research, ticket triage, or back-office workflows end to end.
Semantic search and recommendation over large product catalogs or knowledge bases using embeddings, hybrid retrieval, and reranking.
Document extraction pipelines that pull structured data from contracts, invoices, and PDFs into validated JSON for downstream systems.
When should you hire a LLM Engineer?
- You have an AI feature on the roadmap but no one who has shipped LLMs to production.
- Your RAG prototype works in a demo but hallucinates or returns irrelevant chunks at scale.
- LLM API costs and latency are climbing and you need someone to optimize them.
- You want AI agents and automation but lack expertise in tool calling and orchestration.
How to vet a LLM Engineer: key interview questions
How do you design a RAG system for a large document corpus?
What is the difference between fine-tuning and prompt engineering?
How do you evaluate LLM output quality at scale?
How do you detect, measure, and reduce hallucination in a grounded application?
How do you architect a reliable multi-step agent that calls external tools, and how do you handle failures and retries?
Why hire llm engineers through AILUM?
Pre-vetted senior talent
Every candidate is screened on real skills, system design, and English before you ever meet them. You interview a short, qualified shortlist — not a stack of resumes.
US time zones & English fluency
Our Latin American engineers overlap your full workday and join standups, sprints, and code reviews in real time — collaboration that feels in-house, without offshore lag.
Month-to-month, no lock-in
Scale up or down as your roadmap changes. No recruiting fees, no long-term contracts — start in about a week and only keep the talent that delivers.
Frequently asked questions
Do your LLM engineers have real production experience, not just demos?
Yes. We vet for engineers who have shipped GenAI features that real users depend on, RAG systems, agents, and AI products serving live traffic. During vetting they walk through architecture decisions, evaluation strategy, and the production tradeoffs they made around cost, latency, and reliability, so you get builders, not just prototypers.
Can they control hallucination and manage LLM costs?
Yes. Controlling hallucination through grounding, retrieval quality, reranking, and evaluation harnesses is core to the role. They also manage cost and latency with model selection, caching, prompt optimization, and token budgeting, so your AI features stay accurate and economical as usage grows rather than spiraling unpredictably.
How fast can an LLM engineer start?
Typically within one to two weeks. We maintain a vetted pool of nearshore LLM engineers, so once we understand your stack and goals we shortlist matches quickly. You interview the candidates you like, and engagements are month-to-month with no recruiting fees, so onboarding stays fast and low-risk.
Related roles you can hire
Hire your LLM Engineer — free consultation
Tell us your requirements and we'll match you with pre-vetted candidates within 72 hours.
Start Free — No Commitment