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 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
To Apply
Please send your resume in English.
Include the following depending on your role:
- LinkedIn Profile URL (required)
- GitHub 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 OneSeven Tech
OneSeven 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.
