Hire developers for your exact tech stack

React is how most product companies build their web frontend — from early-stage startups to Fortune 500 engineering orgs. The challenge isn't finding someone who knows React; it's finding someone who knows when not to use useEffect, how to structure a component library that won't become a maintenance nightmare, and how to squeeze performance out of a heavy dashboard. NeuronHire places LATAM React engineers vetted on React 18+, TypeScript, Next.js, and real-world state management patterns — timezone-aligned with US teams, first profiles in 7 days, 30–50% below US rates.

Angular is the choice for teams that want strong conventions enforced by the framework — not by code review. Its opinionated structure, strict TypeScript, and built-in dependency injection make it well-suited for large codebases where inconsistency compounds over time. The challenge is that good Angular engineers who understand RxJS deeply, manage state without over-engineering it, and know the post-v16 signals model are harder to find than Angular generalists. NeuronHire places Angular developers from Latin America vetted on Angular 17+, RxJS, NgRx, and enterprise patterns — timezone-aligned with US teams and 30–50% below US rates.

Vue.js is the frontend framework that product teams reach for when they want React's power without React's ceremony. The Composition API in Vue 3 is genuinely good, Pinia replaced Vuex cleanly, and Nuxt 3 is a serious full-stack framework. Where teams get into trouble is hiring Vue developers who know Vue 2 Options API and calling it done — the Vue 3 Composition API is a meaningfully different mental model and production experience. NeuronHire's LATAM Vue engineers are vetted on Vue 3 specifically: Composition API, Pinia, TypeScript integration, and Nuxt 3 in production. First profiles in 7 days, 30–50% below US rates.

Most React teams hit a wall when they need SSR, fast page loads, and a real backend — and that's exactly when they move to Next.js. The App Router and React Server Components shifted how the framework works, and most developers who list Next.js on a resume haven't actually shipped production apps using them. NeuronHire places Next.js developers from LATAM who are tested on App Router architecture, RSC data patterns, streaming, and full-stack Next.js — not just people who've run create-next-app. Timezone-aligned with US teams, placed in 7 days, at 30–50% below US rates.

TypeScript is now the default for any JavaScript codebase with more than two developers. The static type system catches an entire class of runtime bugs before they reach production, and the IDE tooling alone makes teams faster. The problem is that TypeScript depth varies wildly — plenty of engineers add basic type annotations and call it TypeScript, while the real specialists design type-safe API boundaries with Zod, write conditional types that eliminate unsafe casting, and know when strict mode is hurting more than it's helping. NeuronHire's LATAM TypeScript engineers are vetted on generics, utility types, and real-world applied TypeScript across React, Node.js, and full-stack systems. First profiles in 7 days, 30–50% below US rates.

JavaScript is the only language that runs natively in every browser on the planet — and through Node.js, it runs your backend too. The supply of JavaScript developers is massive, but the supply of engineers who actually understand the event loop, prototype chain, and async model is much smaller than it looks. NeuronHire places pre-vetted JavaScript developers from Latin America — assessed on modern ES2024+, async patterns, the event loop, and real application architecture — in 7 days at 30–50% below US rates.

Node.js is still the dominant backend for JavaScript-first teams — and for good reason. The event loop handles high-concurrency I/O workloads efficiently, startup time is fast enough for serverless, and sharing types across the full stack removes an entire category of bugs. But the gap between a developer who knows Node.js and one who actually understands the event loop, async error propagation, and memory management is significant. NeuronHire places Node.js developers from LATAM vetted on Express, NestJS, production API design, and async patterns under real load. Placed in 7 days, at 30–50% below US rates.

Python is the dominant language across three very different disciplines — backend APIs, data engineering, and ML/AI — which makes specialization matter. A great FastAPI engineer and a great PySpark engineer both write Python, but they're not interchangeable. NeuronHire places Python developers from LATAM who are vetted by discipline: backend (Django, FastAPI), data engineering (Pandas, PySpark, Airflow), and ML/AI (PyTorch, LangChain, scikit-learn). Timezone-aligned with US teams, placed in 7 days, at 30–50% below US rates.

Java dominates enterprise backend engineering — banking, insurance, e-commerce, and SaaS platforms at scale all run on it. The Spring ecosystem, JVM performance characteristics, and decades of production hardening make Java the default choice when reliability and team size both matter. NeuronHire places pre-vetted Java developers from Latin America — assessed on Spring Boot, microservices patterns, JPA/Hibernate, and cloud-native Java — in 7 days at 30–50% below US rates.

Most companies running Microsoft-stack backends can't afford to wait months for a senior .NET hire — yet that's exactly what the US market forces on you. .NET powers the APIs, identity systems, and Azure-integrated services that keep enterprise SaaS and fintech platforms running. NeuronHire places pre-vetted .NET engineers from Latin America — aligned to your timezone, fluent in C# 12+, ASP.NET Core, EF Core, and modern .NET 8+ patterns — in 7 days at 30–50% below US rates.

Go was built for the kind of infrastructure problems that break other languages — high concurrency, fast startup, tiny binaries, and predictable performance under load. It's the language behind Kubernetes, Docker, and Terraform for a reason. NeuronHire places pre-vetted Go developers from Latin America — assessed on idiomatic Go, goroutines and channels, gRPC, and cloud-native patterns — in 7 days at 30–50% below US rates.

PHP gets dismissed by engineers who haven't looked at it since 2012, but the reality is it runs more than 75% of the web — including WordPress, WooCommerce, Drupal, and a substantial portion of the world's SaaS businesses built on Laravel. Modern PHP 8.3 is typed, fast, and nothing like the PHP that earned its bad reputation. NeuronHire places PHP developers from LATAM vetted on PHP 8.3+, Laravel, Symfony, and production API design — including developers who specialize in modernizing the legacy codebases most companies actually have. Placed in 7 days, at 30–50% below US rates.

Rails is still the fastest way to build a full-featured web product from scratch — convention over configuration means a small team ships what takes months in other stacks in weeks. GitHub, Shopify, and Basecamp still run on it, and Rails 7 with Hotwire has made the modern frontend question largely irrelevant for most SaaS products. The shortage isn't Rails developers — it's Rails developers who know the performance traps, the N+1 landmines, and how to keep a five-year-old Rails codebase from becoming a liability. NeuronHire's LATAM engineers are vetted on exactly that. First profiles in 7 days, 30–50% below US rates.

If your product lives on iPhone, you need engineers who know Swift cold — there's no shortcut. iOS development demands deep platform knowledge: SwiftUI, Combine, CoreML, and the App Store submission process all require hands-on experience that cross-platform tools can't fully replace. NeuronHire places pre-vetted iOS developers from Latin America — assessed on Swift 5.9+, SwiftUI, UIKit, Combine, and App Store deployment — in 7 days at 30–50% below US rates.

Native Android development is non-negotiable when your app depends on hardware integration, Google services, or performance that cross-platform frameworks can't match. The Kotlin ecosystem has matured fast — Coroutines, Flow, Jetpack Compose, and the Jetpack library suite have raised the skill ceiling considerably. NeuronHire vets Android Kotlin developers from Latin America on architecture patterns (MVVM/MVI), Jetpack Compose, Coroutines, and Play Store release workflows. They're timezone-aligned with US teams and cost 30–50% less than equivalent US hires.

Maintaining separate iOS and Android teams is expensive — React Native lets one team ship to both platforms without sacrificing native feel. That's why it's the default mobile framework for most product teams that aren't building something deeply platform-specific. The gotcha is that React Native experience isn't evenly distributed: plenty of devs can build basic screens, but far fewer know how to debug bridge performance, write a native module, or navigate the EAS Build configuration maze. NeuronHire's LATAM engineers are vetted on exactly those areas. First profiles in 7 days, 30–50% below US rates.

Maintaining separate iOS and Android codebases doubles your mobile engineering cost — and for most product teams, that's not a trade-off worth making. Flutter lets you ship pixel-perfect, high-performance apps across mobile, web, and desktop from a single Dart codebase without the UX compromises of earlier cross-platform tools. NeuronHire places pre-vetted Flutter developers from Latin America — vetted on Flutter 3+, Riverpod, BLoC, and multi-platform deployment — in 7 days at 30–50% below US rates.

When your data team's bottleneck is volume — terabytes of raw events, petabyte-scale joins, ML training on datasets that don't fit on one machine — Spark is what you reach for. It's the engine behind most serious data engineering and ML infrastructure at scale. The gap between a Spark engineer who can write a PySpark job and one who can tune it — managing partitions, avoiding shuffles, optimizing join strategies — is enormous and shows up directly in cluster costs and pipeline SLAs. NeuronHire's LATAM Spark engineers are vetted on PySpark, Structured Streaming, Delta Lake, and Databricks deployment. First profiles in 7 days, 30–50% below US rates.

When your data pipelines break at 2am and nobody knows why, you need an engineer who can design Airflow DAGs that are observable, testable, and built to survive production. Most companies hit Airflow's complexity wall — custom operators, dynamic DAGs, Celery vs. Kubernetes executors — and realize they need a specialist, not a generalist who's touched it once. NeuronHire places Airflow engineers from Latin America vetted on DAG design, Astronomer/MWAA/Cloud Composer deployments, and pipeline architecture. They're timezone-aligned with US teams and cost 30–50% less than equivalent US hires.

Snowflake is the cloud data warehouse most analytics-forward companies land on when they outgrow Postgres or BigQuery — and for good reason. The elastic compute model means you're not paying for idle capacity, and the separation of storage and compute means your BI team isn't fighting your ETL jobs for resources. The problem is that Snowflake is easy to get running and expensive to get wrong — warehouse sizing, clustering keys, and query patterns have a direct impact on your monthly bill. NeuronHire's LATAM Snowflake engineers are vetted on SQL optimization, data modeling, Snowpark, and dbt integration. First profiles in 7 days, 30–50% below US rates.

Databricks is where organizations land when they need serious data processing volume and ML in the same platform — the Spark engine, Delta Lake storage, MLflow for model lifecycle, and Unity Catalog for governance work together in a way that separate point solutions can't match. The challenge is that Databricks expertise runs deep: Spark performance tuning, Delta Live Tables design, Unity Catalog governance setup, and cluster cost management are all distinct skills. NeuronHire places Databricks engineers from Latin America vetted on Spark, Delta Lake, Workflows, Unity Catalog, and MLflow. Placed in 7 days at 30–50% below US rates.

When your microservices need to talk to each other at scale without tight coupling, Kafka is usually the answer. It handles millions of events per second with durable, ordered logs that multiple consumers can read independently — no other tool matches it for real-time data pipelines and event-driven architecture. The catch is that Kafka requires engineers who deeply understand partitioning, consumer group design, and exactly-once semantics, or you end up with subtle data loss bugs in production. NeuronHire places pre-vetted Kafka engineers from LATAM in 7 days at 30–50% below US rates — assessed on Confluent Platform, Kafka Streams, Schema Registry, and cluster operations.

dbt has become the standard for SQL-based transformations in the modern data stack because it finally brought software engineering practices — version control, testing, documentation, CI/CD — to analytics work that was previously living in someone's personal SQL scripts. The real value is in the modeling layer: an experienced dbt engineer designs a project structure that scales, writes tests that actually catch data quality issues, and keeps metric definitions consistent across every downstream consumer. NeuronHire places dbt engineers from Latin America vetted on dbt Core, dbt Cloud, dimensional modeling, and integration with Snowflake, BigQuery, and Redshift. Placed in 7 days at 30–50% below US rates.

Building a proof of concept with the OpenAI API takes an afternoon. Building a production AI feature that's reliable, cost-efficient, and doesn't hallucinate on your customers takes a real engineer. The work is in prompt architecture, output validation, RAG pipeline design, cost control, and observability — not just the API call. NeuronHire places OpenAI API specialists from LATAM who are vetted on the full stack: GPT-4o chat completions, the Assistants API, function calling, structured outputs, embeddings, and fine-tuning for domain-specific accuracy. First candidates in 7 days, at 30–50% below US rates.

Claude Code is Anthropic's agentic coding CLI and IDE integration — it lets Claude autonomously read, write, run, and debug code inside your actual development environment. Engineers who specialize in Claude Code aren't just prompt engineers — they build production automation: MCP servers that connect Claude to internal tools, hooks that enforce workflow policies, headless pipelines that run in CI without human intervention. NeuronHire places Claude Code specialists from Latin America vetted on agentic workflows, MCP server development, and CI/CD automation. Placed in 7 days at 30–50% below US rates.

Google's Gemini isn't just another LLM — it's the only major model with native multimodal understanding and a 2 million token context window built in. For teams already running on Google Cloud, Vertex AI makes Gemini the path of least resistance for enterprise-grade AI features. NeuronHire places pre-vetted Gemini engineers from Latin America — assessed on the Gemini API, Vertex AI pipelines, multimodal workflows, RAG, and Gemini's grounding capabilities — in 7 days at 30–50% below US rates.

OpenClaw hit 250,000 GitHub stars in under four months — the fastest adoption curve of any developer framework in recent memory. It's the first autonomous agent runtime that actually works for real-world tasks: reading codebases, running tests, browsing the web, and calling APIs with an LLM as the decision-maker. The engineers who know how to deploy it safely and extend it for enterprise use are rare. NeuronHire places OpenClaw engineers from LATAM vetted on tool integration, multi-agent coordination, and secure production deployment including NemoClaw sandboxing. First candidates in 7 days, at 30–50% below US rates.

CrewAI is the framework teams reach for when they need multiple AI agents working together on a problem — each with a defined role, a set of tools, and a specific job in a larger workflow. The jump from a working demo to a production multi-agent system is significant: you need engineers who understand task delegation patterns, tool reliability, inter-agent communication, and how to handle the failure modes that LLMs introduce. NeuronHire places CrewAI engineers from Latin America vetted on crew design, tool integration, and production deployment of multi-agent systems. Placed in 7 days at 30–50% below US rates.

Most teams building LLM features reach for LangChain first — it's the most widely adopted framework for RAG systems, agents, and multi-step AI workflows, and it dramatically cuts the boilerplate of connecting LLMs to your data and tools. The challenge is that LangChain's abstractions can hide complexity that bites you in production: context window management, retrieval quality, agent reliability, and cost control all require engineers who understand what's happening under the hood. NeuronHire places senior LangChain developers from LATAM in 7 days at 30–50% below US rates — vetted on LangGraph, LangSmith, RAG pipeline architecture, and multi-agent design.

Basic LangChain agents fall apart on anything more complex than a few tool calls — they lack state persistence, reliable branching, and the ability to pause for human review. LangGraph solves this by modeling agent workflows as graphs where nodes are execution steps and edges are conditional transitions, giving engineers precise control over what happens at every step. It's become the standard for teams building production agentic systems that actually need to work reliably. NeuronHire places pre-vetted LangGraph engineers from LATAM in 7 days at 30–50% below US rates — assessed on graph design, state management, multi-agent coordination, and LangGraph Cloud deployment.

When companies need to build accurate LLM applications over their own data — contracts, documentation, financial records, support tickets — LlamaIndex is the framework purpose-built for the job. It handles the full data pipeline from ingestion through chunking, embedding, indexing, retrieval, and synthesis, with more opinionated and production-ready abstractions than LangChain for pure RAG work. The engineers who get results know that basic vector search is rarely good enough — chunking strategy, reranking, and hybrid retrieval are what separate accurate systems from expensive demos. NeuronHire places pre-vetted LlamaIndex engineers from LATAM in 7 days at 30–50% below US rates — vetted on advanced retrieval, query engines, data agents, and evaluation with RAGAS.

Every serious AI application that retrieves private knowledge before generating a response needs a vector store — and Pinecone is the managed option most teams reach for because it handles the infrastructure, scales to billions of vectors, and doesn't require managing your own ANN index. The real work is in the RAG architecture: chunking strategy, embedding model selection, namespace design, hybrid search, and metadata filtering. NeuronHire places vector database engineers from LATAM vetted on Pinecone, pgvector, and the full RAG stack. First candidates in 7 days, at 30–50% below US rates.

Running LangChain or LangGraph in production without LangSmith means debugging blind — you can't see which prompts fired, what the model actually returned, or where your pipeline is losing accuracy. LangSmith traces every LLM call with full context, lets you build evaluation datasets from real traffic, and catches prompt regressions before users notice. It's the tool that turns an LLM application from a black box into something you can actually maintain and improve. NeuronHire places pre-vetted LangSmith engineers from LATAM in 7 days at 30–50% below US rates — assessed on tracing integration, evaluator design, automated testing workflows, and prompt management.

Once you ship an LLM application to production, you need to know what it's actually doing — which prompts fired, what the model returned, where latency came from, and whether outputs are getting worse as traffic grows. LangFuse answers those questions for any LLM framework, not just LangChain, and its self-hosted deployment option is the reason teams in healthcare, finance, and government choose it over LangSmith. NeuronHire places pre-vetted LangFuse engineers from LATAM in 7 days at 30–50% below US rates — assessed on SDK integration, evaluation pipeline design, self-hosted deployment, and LLMOps workflows.

When data science teams run dozens of experiments a week without a disciplined tracking system, they spend more time re-running experiments than building models — and can't reliably reproduce the one that actually worked. MLflow solves this with experiment tracking, model versioning, and a deployment-ready model registry that brings engineering discipline to the ML lifecycle. It's also become the standard in Databricks environments, so any team on that platform needs engineers who know it well. NeuronHire places pre-vetted MLflow engineers from LATAM in 7 days at 30–50% below US rates — assessed on Tracking, Model Registry, Databricks managed MLflow, and LLM evaluation with MLflow 2.x.

Weights & Biases is the experiment tracking platform serious ML teams run — because training a model without it is like deploying code without logs. Every training run logged, every hyperparameter tracked, every artifact versioned. The teams that use W&B properly don't just track metrics — they use Sweeps to automate hyperparameter search, Artifacts to version datasets and models, and W&B Weave to trace and evaluate LLM applications. NeuronHire's LATAM engineers are vetted on the full W&B stack, including Weave for LLM tracing. First profiles in 7 days, 30–50% below US rates.

n8n has quietly become the go-to automation platform for technical teams who outgrew Zapier but don't want to build everything from scratch. It's self-hostable, code-extensible, and now has native LLM nodes — which means the right engineer can wire together AI-powered business workflows in days, not months. NeuronHire places n8n engineers from LATAM vetted on workflow architecture, custom node development in TypeScript, AI/LLM integration, and self-hosted Docker deployments. First candidates in 7 days, at 30–50% below US rates.

Make is what you reach for when you need to automate complex business processes across your SaaS stack without writing custom API integration code — and you've already hit the ceiling of what Zapier can do. Its router, iterator, aggregator, and error handling modules handle the kind of conditional, multi-branch automation that keeps breaking in simpler tools. With native AI modules for OpenAI and Anthropic, it's also become a practical platform for teams shipping AI-enhanced workflows without a full engineering build. NeuronHire places pre-vetted Make engineers from LATAM in 7 days at 30–50% below US rates — vetted on advanced scenario design, AI module integration, error handling, and enterprise automation patterns.

Zapier connects 7,000+ apps and handles the automation work that would otherwise fall between engineering sprints or get done manually every week. The platform has grown well beyond simple two-step Zaps — AI Actions, Tables, Interfaces, and multi-path branching logic mean a skilled Zapier engineer can automate complex ops workflows without a single line of code. The difference between a basic Zapier user and a Zapier engineer shows up in error handling, logic branching, webhook architecture, and building automations that survive edge cases. NeuronHire's LATAM engineers are vetted on advanced Zap design, AI integration, and enterprise automation patterns. First profiles in 7 days, 30–50% below US rates.

TensorFlow is Google's production ML platform — the backbone of large-scale model training and serving at companies that need repeatable, auditable ML pipelines, not just notebooks that run once. While PyTorch dominates research, TensorFlow and TFX own a large share of enterprise ML infrastructure, especially on Google Cloud. The engineers who matter aren't the ones who can write a training loop — they're the ones who can design a TFX pipeline, tune distributed training across TPUs, and ship a model to TensorFlow Serving without a 400ms latency regression. NeuronHire's LATAM engineers are vetted on exactly those skills. First profiles in 7 days, 30–50% below US rates.

If you're training models, fine-tuning LLMs, or building production ML systems, PyTorch is almost certainly what your team runs. It's the framework behind Llama, Mistral, Stable Diffusion, and the majority of serious ML research that makes it to production. The hard part isn't knowing PyTorch — it's finding engineers who've actually debugged distributed training jobs, optimized CUDA memory, and shipped models to prod without blowing up latency. NeuronHire's LATAM engineers are vetted specifically on those depth areas: PEFT, LoRA, FSDP, torch.compile, and TorchServe. First profiles in 7 days, 30–50% below US market rates.

If you're building AI features on open-source models instead of paying per-token to OpenAI, Hugging Face is where your engineers live. The Transformers library and model hub give teams access to Llama, Mistral, Gemma, Whisper, and thousands of other models — with PEFT fine-tuning, quantization, and production inference tooling built in. NeuronHire places pre-vetted Hugging Face developers from Latin America — assessed on the Transformers library, PEFT/LoRA fine-tuning, model deployment, and Inference Endpoints — in 7 days at 30–50% below US rates.

AWS is where most companies' infrastructure already lives, which means AWS engineers aren't a nice-to-have — they're the people keeping your system running and your cloud bill under control. The gap between an AWS engineer who can click through the console and one who can design a secure, cost-efficient, multi-account architecture with IaC from day one is enormous. NeuronHire places AWS engineers from Latin America vetted on core services, Terraform, EKS, security best practices, and production architecture. Timezone-aligned with US teams, at 30–50% below US rates.

Google Cloud is where the most data-intensive and AI-heavy workloads run — BigQuery, Vertex AI, and GKE are genuinely best-in-class for their categories, not just checkbox features. Companies that pick GCP and then can't find engineers who know it cold end up paying AWS-level costs without AWS-level talent availability. NeuronHire places pre-vetted GCP engineers from Latin America — assessed on GKE, BigQuery, Dataflow, Vertex AI, and Terraform for GCP — in 7 days at 30–50% below US rates.

If your company runs on Microsoft — Active Directory, Office 365, SQL Server, .NET — Azure isn't just a cloud option, it's the logical extension of your existing infrastructure. Azure engineers who can navigate Entra ID, AKS, Azure DevOps pipelines, and IaC with Bicep or Terraform are the engineers who make enterprise cloud migrations actually land. NeuronHire places Azure engineers from Latin America vetted on AKS, Azure Functions, Azure DevOps, identity management, and Azure security best practices — timezone-aligned with US teams at 30–50% below US rates.

Docker is the baseline for modern software delivery — if your app isn't containerized, you have environment drift, inconsistent CI builds, and a deployment process that depends on tribal knowledge. But there's a wide gap between someone who can write a Dockerfile and someone who can design production-grade containers: multi-stage builds that minimize attack surface, optimized layer caching that cuts CI time in half, and security hardening that passes a container audit. NeuronHire places Docker engineers from Latin America vetted on Dockerfile optimization, Docker Compose, container security, and CI/CD integration. Placed in 7 days at 30–50% below US rates.

Kubernetes is how serious engineering teams run containerized workloads in production — handling deployment, scaling, self-healing, and networking across cloud infrastructure without manual server intervention. The problem is that Kubernetes has a steep learning curve: a misconfigured RBAC policy or a missing resource limit can take down a cluster, and debugging a failing pod across namespaces requires genuine expertise. NeuronHire places senior Kubernetes engineers from LATAM in 7 days at 30–50% below US rates — vetted on Helm, GitOps with ArgoCD, EKS/GKE/AKS, RBAC, and platform engineering patterns.

Terraform is how serious engineering organizations manage cloud infrastructure — replacing manual console configurations with versioned, reviewable, repeatable code. The difference between a team that uses Terraform and one that uses it well shows up in incident response: when infrastructure is code, you can audit every change, roll back a bad deployment, and spin up a staging environment that exactly mirrors production. NeuronHire's LATAM Terraform engineers are vetted on module design, state management, Terragrunt, and multi-cloud patterns. First profiles in 7 days, 30–50% below US rates.

MySQL is still running the backends of some of the highest-traffic systems on the internet — and that means the bar for who you hire to touch it is high. A bad index or a poorly designed replication setup doesn't surface in dev; it surfaces at 3am on Black Friday. NeuronHire places MySQL engineers from LATAM who are vetted on InnoDB internals, query optimization with EXPLAIN, replication topology, and managed MySQL on RDS and PlanetScale. You get your first candidates in 7 days, at 30–50% below US rates.

Redis shows up in almost every high-performance production stack — as a cache, a session store, a rate limiter, a job queue, a pub/sub broker, or all five at once. The risk isn't adopting Redis; it's adopting it without someone who understands cache invalidation pitfalls, cluster failover, and what happens to your data when persistence is misconfigured. NeuronHire's LATAM Redis engineers are vetted on data structures, cluster mode, Pub/Sub, Lua scripting, and Redis Stack. First profiles in 7 days, 30–50% below US rates.

PostgreSQL is the default database for most new production applications — and for good reason. ACID transactions, JSONB, full-text search, logical replication, and pgvector for AI workloads are all first-class. But the gap between a developer who can write SQL and an engineer who can design a schema that performs at scale, tune indexes correctly, and set up replication without data loss is significant. NeuronHire places PostgreSQL engineers from LATAM vetted on schema design, query optimization with EXPLAIN ANALYZE, partitioning, replication, and pgvector. Placed in 7 days at 30–50% below US rates.

MongoDB is the right database when your data is naturally document-shaped, your schema is still evolving, or you need horizontal sharding that PostgreSQL can't give you without significant engineering overhead. The risk is that MongoDB's flexibility is a double-edged sword — teams without experienced engineers often end up with schema designs that kill query performance or aggregation pipelines that run in minutes instead of milliseconds. NeuronHire places pre-vetted MongoDB engineers from LATAM in 7 days at 30–50% below US rates — vetted on schema design, aggregation pipelines, Atlas, indexing strategies, and MongoDB Atlas Search.

Bad search kills conversion — and most teams only realize how bad their Elasticsearch configuration is when load spikes or relevance complaints pile up. Elasticsearch powers full-text search, log analytics, APM, and vector similarity search across some of the highest-traffic systems in the world. NeuronHire places pre-vetted Elasticsearch engineers from Latin America who know index design, query DSL, ELK/Elastic Stack operations, and production tuning — in 7 days at 30–50% below US rates.