Remote Forward-Deployed AI Engineer

FullStack; Capital; A distancia; COP 300.060.000 - 500.100.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive salary

Paid time off

100% remote work

English classes

Career advancement

Descripción de la vacante

FullStack is seeking Senior AI/ML engineers to join our 100% remote team. You’ll work inside client ecosystems, designing robust AI-powered solutions, building production‑grade systems, and ensuring performance and reliability in real‑world settings.

You’ll combine consulting, engineering, and operations to move ideas from discovery to production, emphasizing retrieval, data quality, and guardrails. The role demands deep experience in ML, data systems, and software engineering across enterprise

Formación

• 8–10+ years across ML, data, and software engineering.
• Python-first, production-grade (typed, tested, deployed services — not notebooks only); working proficiency in TypeScript / Node, .NET / C#, or Java is a plus.
• Track record as an ML/Data Architect, Principal Engineer, or Tech Lead — can assess a data and AI current state and define a credible roadmap.
• Has designed and owned CI/CD for AI or ML systems (LLMOps / MLOps).

Responsabilidades

• Discover. Run workshops and process discovery with business, data, and engineering stakeholders.
• Structure processes and the spec for automation, mapping current state to actionable specs.
• Architect & design end-to-end agentic systems with emphasis on context and retrieval architecture.
• Build working systems: agents, retrieval services, evaluation tooling, data flows.
• Operate (Day 2): ensure monitoring, governance, and handoff to the client team.
• Consult: defend decisions with CTOs and senior leaders, shaping pre-sales and proposals.

Descripción del empleo

FullStack is seeking Senior AI/ML engineers to join our 100% remote team. You’ll work inside client ecosystems, designing robust AI-powered solutions, building production‑grade systems, and ensuring performance and reliability in real‑world settings.

You’ll combine consulting, engineering, and operations to move ideas from discovery to production, emphasizing retrieval, data quality, and guardrails. The role demands deep experience in ML, data systems, and software engineering across enterprise