Deployment Strategist - Chile
Apply at source. ElevenLabs handles the application directly; Houtini doesn't take a fee from candidates or companies. We curate which companies appear; the listings come from yubhub.
What the team is looking for.
As a Deployment Strategist, you'll work as part of a driven and creative team to deploy ElevenAgents, our enterprise AI platform, against the challenging problems our customers face.
Your mission is to synthesize disconnected streams of thought into a cohesive understanding of what the most important problem is, what the existing workflows are, what the product needs, what users are motivated by, and where the impact could be.
Responsibilities:
- Own flagship deals end-to-end , from identifying the right use case to structuring commercial terms and driving them to close.
- Embed yourself deeply inside strategic customers: act as a trusted partner with a provisioned account, spend meaningful time onsite, and own delivery outcomes as if you were part of their team.
- Identify high-impact use cases through close engagement with customer problems and workflows, and collaborate with Forward Deployed Software Engineers to bring them to life.
- Guide customers on best practices for deploying our products; including agent design, agent orchestration, production readiness to maximize adoption and impact.
- Scope out potential applications in new industries and expand our AI solutions across different sectors globally.
- Present the results of our work and proposals for future work to audiences ranging from technical teams to C-suite executives.
- Collaborate with our Research teams to feed field insights back into ElevenLabs' platform and models, helping shape the roadmap.
- Build and deliver compelling demos of ElevenAgents and our broader AI technology to new and existing customers.
- Collaborate daily with customers' engineering and executive teams to ensure agents reach production and deliver measurable business outcomes.
Requirements:
- 3+ years of experience working with customers in a technical capacity. Direct enterprise customer experience is preferred.
- Experience in product development, delivery, and change management.
- Commercial instinct: comfort engaging in deal conversations, structuring value propositions, and navigating enterprise sales cycles alongside GTM partners.
- Basic proficiency in Python and familiarity with API integration, sufficient to prototype, demo, and communicate credibly with engineering teams.
- Excellent communication and problem-solving skills; particularly the ability to simplify complex technical concepts and structure clear logic in pursuit of optimal solutions.
- A proven track record of taking ownership of complex, ambiguous projects and delivering results.
- Adaptability to work across different customer environments, industries, and technical use cases.
- Technical aptitude and familiarity with common LLM, tooling and AI agent frameworks.
- Ability to creatively map enterprise use cases and workflows to AI systems.
- Python
- API integration
- product development
- change management
- commercial instinct
- problem-solving
- enterprise customer experience
- LLM
- AI agent frameworks
Other roles you might consider.
Filtered through the same AI-companies allowlist.
Enterprise Solutions Engineer - Chile
ElevenLabs
Deployment Strategist - Chile
ElevenLabs
Enterprise Solutions Engineer - Chile
ElevenLabs
ML Platform Engineer
Synthesia
Enterprise Solutions Engineer - Chile
ElevenLabs
Technical Specialist, Claude Code
Anthropic
New to AI work? Start with these.
Six pieces of orientation. Most AI-company job specs assume you've done this kind of hands-on work already. If you haven't, an afternoon with one of these is the cheapest way to close the gap.
Claude Desktop, from zero.
The agentic-AI assistant most of the people you'd be working alongside use every day. Install, configure, first useful prompts.
What MCPs areThe best MCPs for Claude Desktop.
MCP servers extend an AI assistant with tools and data. The catalogue most teams use. Useful technical context for any AI-engineering role.
Code with AIClaude Code, the complete beginners' guide.
The CLI for AI-paired development. Required reading if you're applying for any engineering role that mentions agents, or any role full stop.
Run a local modelHow to set up LM Studio.
Running a model on your own machine teaches you more about how AI products work in three hours than a year of using ChatGPT will.
The hardware realityBeginner's guide to AI hardware.
What the infrastructure under the model actually looks like. Useful context for infrastructure, applied-AI and hardware roles.
Browse the stackMCP catalogue.
Eleven MCP servers Houtini maintains or recommends. Each detail page describes a real piece of working AI infrastructure.