AI/ML Engineer — MCP

**We're building out a Model Context Protocol (MCP) infrastructure for a mid-market US software company that's moving fast into agentic AI. This is a new, independent engineering team — separate from existing projects — building from the ground up. Your role has a strong DevOps lean: keeping the MCP infrastructure healthy, observable, and scalable as agents and tools get added. You'll own deployments, pipelines, and production stability. The title is flexible — what matters is the function: someone who can hold the technical ground on infrastructure while the team builds.

Must-Haves

• Strong DevOps fundamentals in practice — you own deployments, not just contribute to them. Container orchestration (Docker + ECS/Fargate or equivalent), GitHub Actions for CI/CD, AWS (ECS, RDS, S3, CloudWatch), and MCP protocol familiarity are part of your daily work.
• Hands-on production experience with LangChain, LangSmith, and/or LangGraph — not course projects or prototypes
• LLM infrastructure thinking — you understand token cost, latency tradeoffs, rate limits, and how to monitor them in production
• Comfortable working autonomously in a small team without daily hand-holding
• Near-native English — daily async communication with a US-based technical lead and client stakeholders

Nice to Have

• LangSmith tracing and evaluation features — setting up traces, running evals, interpreting results
• Experience collaborating directly with a client-side senior engineer — comfortable integrating into an established technical dynamic and contributing without needing to redefine it
• Familiarity with observability tooling beyond CloudWatch — Datadog, Grafana, or similar

What You Will Do

• Monitor, maintain, and optimize the agentic infrastructure running on LangChain / LangSmith / LangGraph
• Manage container-based deployments and ensure stability across environments
• Build and own CI/CD pipelines for agent and model deployments
• Set up and maintain observability — tracing, alerting, and performance dashboards for LLM-based systems
• Support MCP server integration as the client-side team ships new components
• Identify and resolve latency, cost, and reliability issues before they become production incidents
• Work closely with the client's MCP technical lead — small team, no bureaucracy, your infrastructure decisions are immediately visible

Why This Could Be Your Next Big Move
🏗️ Infrastructure that actually matters — You're not maintaining a toy. This is a production agentic system with real users, real costs, and real consequences when things break.
🔍 Observability as a craft — LLM systems fail in non-obvious ways. You'll build the tooling that makes invisible problems visible before the client notices them.
🤝 Direct access to the technical decision-makers — Small team, no bureaucracy. Your work is immediately visible to the client's lead engineer and a senior technical advisor
🚀 MCP is the frontier — Model Context Protocol is where enterprise AI is heading. You'll have production experience on it before most engineers have even read the spec.

Benefits & Compensation
💵 $4000 - $5000/month — paid in USD, bi-weekly via Deel
🕐 US Eastern Time hours (EST) — Monday to Friday, 9:00 AM–6:00 PM EST

🌎 Fully Remote — work from anywhere in Latin America
📄 Long-term contract — starting with a 6-month contract, with potential to extend
🏖️ Paid PTO — accrual begins after 3-month trial period
🤝 Referral Program — earn a bonus for referring talent that gets hired