Hire senior AI agent developers who ship agents to production
Senior engineers who design agentic systems with bounded tools, human approval steps and evals, so agents do useful work without surprising anyone.
By the Ryz Labs team · Updated October 2026
Hiring AI agent developers through Ryz gets you senior Latin American engineers who build agents that take real actions in your systems, with scoped tools, approval steps and evaluations that catch regressions. They are the top 1% of the engineers we interview, and they work on your team and in your repos within an hour of US time zones.
What our AI agent developers work on
An agent is a model running in a loop, choosing tools until a task is done. The model is the easy part. The hard parts are deciding what each tool may do, recovering from failures, keeping costs bounded and proving the agent behaves. Our developers build agents with the Claude Agent SDK, the OpenAI Agents SDK, LangGraph, Google's ADK or a plain loop, whichever fits. Typical projects:
- Support agents that look up orders, issue refunds within limits and escalate to a person with a summary.
- Operations agents that triage tickets, gather logs and draft fixes for an engineer to approve.
- Research agents that search internal and web sources and produce a cited brief.
- Back-office agents that reconcile invoices, flag anomalies and prepare work for reviewers.
- Coding agents in CI that review pull requests, write tests or perform routine migrations.
- Multi-agent setups with an orchestrator delegating to specialists, where a single agent has hit its limits.
Skills we vet for
- Tool design. Small, well-named tools with typed inputs, clear error messages and idempotent writes.
- Permission and blast radius. Read versus write tools, per-user credentials, spending limits and approval gates before irreversible actions.
- Context engineering. What goes into the context window at each step, summarizing long histories and memory that does not leak between users.
- Control flow. When to use a fixed workflow, a single agent loop or multiple agents, and how to cap steps and cost.
- Protocols. MCP for connecting tools and data, and A2A where agents from different systems need to talk.
- Evals for agents. Task success rates, trajectory checks, simulated users and regression suites on every change.
- Security. Prompt injection through tool results, data exfiltration risks and sandboxing code execution.
- Observability. Traces of every step with OpenTelemetry, Langfuse or LangSmith, so failed runs can be replayed.
How we vet AI agent developers
Recruiters source engineers who have put agents in front of real users or real systems, then our in-house ARC system ranks the pipeline. Candidates take structured NTRVSTA AI interviews on agent architecture, safety and failure analysis. Recruiters review every candidate before and after, and send a curated shortlist. AI scores are advisory; people make the call.
Sample interview topics
- A web page the agent reads contains hidden instructions to email customer data. Which parts of your design stop that from working?
- Your refund agent succeeds 92% of the time in evals. How do you find out what the other 8% have in common, and which failures are unacceptable?
- Design an agent that books travel within policy. Which tools exist, which need approval and what happens if the booking API fails after payment?
- When does splitting one agent into several make things worse?
- How do you keep an agent's cost per task predictable when it can choose how many steps to take?
Ways to hire AI agent developers
| Option | Best for | Trade-offs |
|---|
| Freelance marketplace | An agent demo for internal buy-in | Demos rarely include permissions, evals or failure handling. Production is a different project. |
| Staffing or recruiting agency | Sourcing AI engineer resumes | "Agent experience" is hard to verify from a resume, and most screens do not test it. |
| In-house recruiting | A permanent agent platform team | Slow to hire, and few internal interviewers know what to probe. |
| Ryz Labs staff augmentation | Adding agent experience to a product or platform team | You direct priorities and review code. Best when the target workflow is known. |
| Ryz Labs AI pod team | Taking an agent from idea to production inside your cloud | A dedicated pod with a tech lead, ML and backend engineers and weekly demos. Scoped up front. |
Ryz is the wrong fit if you want to license an agent platform rather than have engineers build in your stack, or hourly gigs booked without a conversation. Teams that need Europe or Asia hours should look at global networks.
Why hire AI agent developers from Latin America
Agents change how work gets done, so every rollout involves the people whose work changes. Developers in your time zone can watch operators use the agent, hear where it gets in the way and adjust tools and approvals in the same week.
The engineers we place have years of experience building integrations and backend systems for US companies, which is most of what an agent touches. Our pod teams have shipped agents in production, including a driver-support agent that covers roughly 218,000 driver calls a year in three languages and a real-estate agent that works around the clock. Details are in our case studies.
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FAQ
Which agent framework do you use?
Whatever fits your stack and the problem. Our developers work with the Claude Agent SDK, the OpenAI Agents SDK, LangGraph, Google's ADK and custom loops. Sometimes a fixed workflow is better than an agent, and we will say so.
How do you keep agents from doing something harmful?
By limiting what tools can do, requiring approval before irreversible actions, treating tool output as untrusted input and testing against adversarial cases before launch.
How is pricing set?
Custom quote, scoped per team. Before signing, you get a plan, a price and the names of the people who would do the work.
How do Ryz engineers work with our team, and what hours do they keep?
Ryz engineers work on your team, reporting to your leads. They work within an hour of US time zones. Talk to us to scope your team.
Questions we didn't answer? Email info@ryzlabs.com.