Forward Deployed AI Engineer

Key Responsibilties

• Sit with the client's operators and execs, ask sharp questions, and turn fuzzy automation requests into concrete, shippable plans with clear judgment on what not to automate.
• Build production AI agents with real error handling, retries, idempotency, fallbacks, and human-in-the-loop checkpoints across orchestration tools and custom code.
• Build the intelligence layer using LangChain, LangGraph, RAG, structured outputs, and voice agents where they fit the use case.
• Integrate with the real world: REST APIs, webhooks, OAuth2, CRMs, ERPs, Supabase, Airtable, and Google Workspace to execute write-access operations on live records.
• Own production reliability: debug live agents, instrument logging, track costs, set failure alerts, and keep systems running while clients watch.
• Hold the client relationship by explaining tradeoffs to non-technical stakeholders, pushing back on requests that do not make sense, and keeping them confident to keep buying.
• Codify each build into reusable templates so the next deployment ships faster. Who You Are
• You have 3+ years shipping production software, including real AI and agent work delivered to actual users or clients — you have built it, deployed it, and watched it run in the wild.
• You have shipped at least one real project end to end, scoped it, built it, and owned it when it broke in production.
• You work as an army of one: you scope, build, debug, and ship without hand-holding, formal specs, or a manager pointing the way.
• Your English is excellent in speech and writing — you run calls with US founders every week and explain technical tradeoffs to non-technical stakeholders with clarity.
• You think in systems and have wrestled production AI against brittle reality: auth failures, flaky data, rate limits, and the unglamorous 80% that is not the happy-path demo.
• You have strong Python plus at least one of JavaScript or TypeScript, and you are fluent with OpenAI and Anthropic APIs, prompt engineering, structured outputs, RAG, and evals. Bonus Points
• Prior work at an AI-automation agency or as a forward-deployed or solutions engineer.
• Shipped Vapi or Retell voice agents in production.
• Experience with vector databases like pgvector or Pinecone.
• Docker and containerization.
• Former technical founder or freelancer who carried your own clients. What Success Looks Like

Projects

Puente Talent Partners connects top Latin American professionals with growing US companies. This role is for one of our US clients, and you would be joining their team directly while being supported by Puente through the hiring process.

Our client is a US AI startup building production AI agents for real customers. They move fast, ship often, and need engineers who can sit inside their world, scope what matters, and own outcomes end to end. This is not a consulting shop or a lab — it is a company that turns AI into revenue.

About the role

You embed with the client as a forward-deployed engineer and own the outcome from fuzzy problem to production agent. You spend your mornings on calls with founders and operators, turning vague automation ideas into concrete plans. You spend your afternoons building, integrating, and debugging. You are half engineer, half consultant, full owner. This role fits someone who ships fast, owns their work, and does not wait to be told what to build next.

Compensation and culture

Competitive USD compensation paid monthly, 100% remote work from anywhere in Latin America, flexible schedule aligned to a US business day, paid time off, and direct exposure to the leadership of a fast-growing US-based talent platform. Here is what to expect after you apply: (1) you will get an email from Puente with a short online assessment and a quick grammar check, (2) you will record three short video answers so we can see how you communicate, (3) if it looks like a fit, our recruiter sets up an interview, (4) shortlisted candidates are introduced to the US client team for final interviews.

Bonus points

Prior experience working with US-based clients or remote-first teams. Strong written and verbal English (C1+). Comfortable with async communication tools (Slack, Loom, Notion). A track record of taking initiative on ambiguous problems and shipping practical solutions without waiting to be told.