AI​/ML Engineer - MCP Infrastructure

Project Brief 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 Dev Ops 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 Dev Ops fundamentals in practice - you own deployments, not just contribute to them. Container orchestration (Docker + ECS/Fargate or equivalent), Git Hub Actions for CI/CD, AWS (ECS, RDS, S3, Cloud Watch), and MCP protocol familiarity are part of your daily work Hands-on production experience with Lang Chain, Lang Smith, and/or Lang Graph - not course projects or prototypesLLM 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 Lang Smith  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 Cloud Watch
- Datadog, Grafana, or similar

What You Will DoMonitor, maintain, and optimize the agentic infrastructure running on Lang Chain / Lang Smith / Lang Graph 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 advisorMCP 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 DeelUS Eastern Time hours (EST) - Monday to Friday, 9:00 AM-6:00 PM ESTFully 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

To Apply Please send your resume in English.

Include the following depending on your role:

Linked In Profile URL (required)
Git Hub repository or project examples (required)
Cover Letter - tell us about an agentic or ML infrastructure project you've maintained or deployed in production, and the hardest infrastructure problem you've had to debug (optional but encouraged)
About One Seven Tech One Seven  Tech is an AI-enabled software agency headquartered in Miami, with 9 years building AI-driven digital products for scaling and established companies. We specialize in consulting, designing, and developing ROI-focused solutions across 22 industries - from healthcare and legal to real estate and fintech.

Our multidisciplinary team blends AI strategy, UX/UI, web and mobile engineering, and machine learning to deliver real outcomes. With 101+ successful projects completed and a 4.9/5 client rating, we work as a deeply embedded partner - not just a vendor. We operate as a remote-first organization with a global team and a US-based client portfolio.
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