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Quiero recibir la alerta de empleo más reciente para reliability engineer en guadalajara, jal

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Senior Applied AI Engineer (LLM & Multi-Agent Systems)

CobaltoTalent
Guadalajara, Jal.

Postulación rápida

Información del empleo

Tiempo completo
Hace 12 días

Cualificaciones

Node.js
Derecho
Experiencia en bases de datos
JavaScript
Empaquetar
S3
TypeScript
Python

Descripción completa del empleo

We are looking for a highly technical Senior Applied AI Engineer to design, build, and scale production-grade AI systems powered by LLMs, multi-agent architectures, and retrieval-based intelligence.

This role is ideal for engineers who have already deployed AI products into real-world environments and understand the operational challenges of production AI systems beyond prototypes or demos.

You will work closely with product and engineering teams to architect reliable, scalable, and observable AI infrastructure capable of serving real users at scale.

What You’ll Build

Production-ready LLM applications and AI workflows
Multi-agent orchestration systems with robust state management
Retrieval-Augmented Generation (RAG) pipelines using vector databases
AI inference orchestration and model routing systems
Structured output pipelines with validation and retry logic
Feedback loops and learning systems for continuous improvement
Scalable multi-tenant AI architectures

Key Responsibilities

Design and implement scalable AI/LLM architectures for production environments
Build reliable multi-agent systems with error isolation and orchestration control
Develop high-performance inference pipelines and AI workflows
Optimize prompt engineering, structured outputs, and function calling
Implement embedding pipelines and retrieval systems using vector databases
Create monitoring, evaluation, and observability frameworks for AI systems
Node.js service integrations
Improve model quality through fine-tuning and evaluation strategies
Ensure scalability, reliability, and cost efficiency across AI services

Required Experience

3+ years of experience building applied AI/ML systems
Proven experience deploying LLM-based applications into production
Strong Python engineering skills in production environments
Experience with async workflows, testing, packaging, and observability
Hands-on experience with Anthropic SDK and/or OpenAI APIs
Experience building RAG systems using vector databases
Strong understanding of AI/agent failure modes:
- hallucinations
- loop control
- state corruption
- cost runaway
Experience designing multi-agent workflows and orchestration systems
Strong system design and architecture fundamentals
Experience designing scalable inference and evaluation pipelines

Technical Stack

Core Stack

Python
OpenAI SDK
Anthropic SDK
pgvector
LangGraph / CrewAI
AWS (S3, ECS, SageMaker)

Nice to Have

Pinecone
Weaviate
Node.js / TypeScript
Fine-tuning on domain-specific datasets
RLHF / RLAIF
Multi-tenant ML architectures

What We’re Looking For

We are looking for engineers who think beyond prompts and prototypes.

The ideal candidate has experience building reliable AI systems that operate in production, can reason about architecture and scalability, and understands the tradeoffs between model quality, latency, reliability, and operational cost.

Important Note

This role is NOT focused on experimentation-only or prompt-only engineering.
We are specifically looking for engineers who have deployed AI systems into production environments.

Why Join Us?

Opportunity to work on cutting-edge AI systems
High technical ownership and architectural impact
Real production-scale AI challenges
Collaborative engineering environment
Fast-moving and innovation-driven team

Postulación rápida

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