7 publicaciones de empleo destacadas en lead ai forward engineer (¡Están contratando!)

Software Engineer
Texas Sports Academy Main —México
- Tiempo completo
- Home Office (Desde casa)
- Doctorado
- Informática
- Inglés
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Talent Operations Lead
ElevenLabs —México
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- Home Office (Desde casa)
- Reclutamiento
Deployment Strategist
Happyrobot Inc. —México
- Tiempo completo
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- Seguro de la vista
Adoption Strategist - LATAM
ElevenLabs —México
- Tiempo completo
- Home Office (Desde casa)
- Inglés
9d
Senior Frontend Engineer (React) - LATAM
AOA —México
- Home Office (Desde casa)
- Inglés
- Licenciatura
- JavaScript
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Senior Android Engineer - LATAM
AOA —México
- Home Office (Desde casa)
- Administración de personal
- Inglés
- C++
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Senior Frontend Engineer (Shopify) - LATAM
AOA —México
- Home Office (Desde casa)
- Inglés
- Licenciatura
- JavaScript
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Software Engineer

Texas Sports Academy Main
México

Postulación rápida

Información del empleo

Tiempo completo

Cualificaciones

Node.js
Derecho
Doctorado
Informática
React
Matemáticas
Inglés
Google Cloud Platform
Maestría
Matemáticas
Licenciatura
PostgreSQL
TypeScript
Python

Descripción completa del empleo

Software Engineer (AI-Forward)

As a Software Engineer with Texas Sports Academy, you play a key role in building the software that runs our school — student records, academic mastery tracking, training data, parent portals, admissions, and the AI-powered tools our guides and coaches use every day. This is a senior, AI-forward seat. You work directly with the founders, ship code every week with AI in your loop, and own the LLM-powered features that make our school feel nothing like a traditional school.

What you will be doing

Designing, building, and shipping product features across the full stack every week, with AI coding tools running alongside you.
Building real LLM-powered product features: tutoring agents, parent-facing copilots, coach-facing dashboards, retrieval over student data, evals for every one of them.
Working directly with the founders on scope, architecture, and trade-offs — no PM layer in between.
Owning the reliability, security, and cost of both classical systems and LLM pipelines.
Running your own AI coding workflow — prompts, subagents, custom tools, MCP servers — and raising the bar on how the whole team uses AI.
Writing evals and regression tests for AI features the same way you'd write unit tests for classical code.

What you will NOT be doing

Pretending AI is optional — if you're not already coding with Claude Code, Cursor, Codex, or an equivalent agent loop every day, this role is not for you.
Writing tickets for junior engineers to implement.
Sitting in status meetings all day — few meetings, more shipping.
Working on a narrow slice of a giant codebase.

Key responsibilities

Ship production code and AI features real students, parents, and staff rely on every day.
Own at least one major system end-to-end.
Move fast — features go from idea to production in days, not quarters — without breaking things.
Raise the AI-engineering bar as the team grows.

Requirements

Bachelor's or master's degree in Computer Science, Engineering, Math, or Physics.
6+ years of full-time production engineering experience shipping software to real users at real scale.
At least one prior senior, staff, or tech-lead role.
Daily, fluent use of AI coding tools (Claude Code, Cursor, Codex, Windsurf, Aider, or equivalent) as your default way of writing software.
At least one shipped LLM-powered feature in production, with an eval story.
Strong skills in a modern web stack (TypeScript / React / Node or Python / Postgres / AWS or GCP).
Excellent written English
Legal authorization to work from India or Pakistan as a remote contractor with a US company.

Nice to have

Master's or PhD from a tier-1 institution.
Former founder, first-five engineer at a funded startup, or shipped products that reached real users at scale.
Agent frameworks (LangGraph, CrewAI, Mastra, custom), vector search / RAG at scale, evals (Braintrust, LangSmith, custom), prompt caching, MCP servers, structured output / tool-use reliability, voice agents.
Public GitHub or a personal AI project we can actually try.
A personal project you built because you wanted to.

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