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LatamCent is seeking a deployment-focused engineer to own the client rollout process from configuration to production. You will work directly with enterprise accounts, driving architecture discussions and ensuring reliable production operations.
You will build monitoring, dashboards, and API integrations while collaborating with product and engineering to close gaps. Strong Python, Docker, Kubernetes, and English skills are required.
A fast-growing AI platform serving enterprise customers is building out its deployment team to own the technical side of client rollouts end-to-end. You'll be the primary technical contact for major accounts, taking AI-powered solutions from configuration to production and keeping them running at scale.
This is not a support role. It's not pre-sales. It's a heavy engineering function with full client ownership — the kind of work where you're in architecture discussions with a CTO one hour and debugging a production incident the next. If you move fast, think in systems, and want your name on the accounts you deploy, this is where that happens.
Lead the full deployment lifecycle for enterprise integrations — from initial client configuration through production go-live and ongoing reliability.
Serve as the primary technical contact for a portfolio of enterprise clients: run architecture discussions, own escalations, and keep systems healthy.
Build and maintain monitoring infrastructure, dashboards, and alerting systems that surface issues before they become client problems.
Own backend and API integrations across enterprise systems, ensuring secure and stable production operation.
Translate client requirements into scalable solutions within platform constraints, and bring patterns back to product and engineering to close gaps.
Drive a data-informed approach to deployments through logging and analytics systems that enable proactive optimization.
2–5 years in a client-facing technical role — solutions engineering, technical consulting, or deployment/implementation. You've owned external relationships, not just supported them.
Python in production — backend services, APIs, automation. Scripting-only experience is not sufficient.
Docker for containerized deployments. Kubernetes experience is a strong plus.
REST API integrations at enterprise scale — day one capability, no ramp-up needed.
Comfortable owning complex enterprise stakeholder relationships independently — from architecture decisions to escalation handling, without hand-holding.
AI-assisted development mindset — you use AI tooling to move faster and expect it to handle the majority of your code.
Native-level English fluency — written and verbal. You'll interface directly with CTOs and senior executives.
PST full business hours availability — based in LATAM, full overlap required.
Background in AI, NLP, or conversational systems
Experience with VoIP, SIP/RTP, CCaaS, or CPaaS platforms
Experience at a contact center technology or voice infrastructure company
Exposure to enterprise backend service architecture and multi-system integrations
Python, Docker, Kubernetes, SIP/RTP, REST APIs & monitoring/observability tooling (*Specifics TBD by client stack)
Location: Remote, Latin America
Time Zone: PST overlap required (full business hours)
Salary: Competitive — share your expectations when you apply.
Type: Contract, full-time
Start: ASAP
An enterprise AI platform that automates customer service interactions at scale, deployed across global enterprise accounts handling tens of thousands of calls daily. The company is well-funded, growing fast, and expanding its deployment team to support a rapidly scaling client base.