11 publicaciones de empleo destacadas en devops engineer (observability) (¡Están contratando!)

GenAI Engineer
EPAM Systems, Inc. —Desde casa
- Home Office (Desde casa)
- Azure
- DevOps
- Inglés
- Vacaciones adicionales o permisos con goce de sueldo
Lead AI Forward Engineer
Thomson Reuters —Ciudad de México, CDMX
- Tiempo completo
- Azure
- DevOps
- Python
Head of Applications Architecture
Citi —Ciudad de México, CDMX
- Tiempo completo
- Azure
- DevOps
- Servicios financieros
4h
Senior GenAI Engineer
EPAM Systems, Inc. —Desde casa
- Home Office (Desde casa)
- Azure
- DevOps
- Inglés
- Vacaciones adicionales o permisos con goce de sueldo
Senior Azure Platform Engineer
Cummins Inc. —Guadalajara, Jal.
- Azure
- Oracle
- Administración de personal
Ingeniero Senior de Plataforma Azure
Cummins Inc. —Guadalajara, Jal.
- Azure
- Oracle
- Administración de personal
ML Engineer — Automation
Aviva Financiera —México
- Tiempo completo
- Home Office (Desde casa)
- Azure
- DevOps
- Inglés
- Vacaciones adicionales o permisos con goce de sueldo
Postulación rápida
Senior Middleware Engineer
Partner One Capital —México
- Home Office (Desde casa)
- Azure
- DevOps
- Java
Postulación rápida
Sr. Backend Engineer (Golang)
Unpack Holdings Limited —México
- Tiempo completo
- Home Office (Desde casa)
- DevOps
- SQL
- Matemáticas
Postulación rápida
6d
Software Development Engineer in Test (SDET)
OrderMesh —México
- Home Office (Desde casa)
- Azure
- Informática
- DevOps
Postulación rápida
Full-stack Lead/Senior Developer (C# + Angular)
Jalasoft —México
- Tiempo completo
- Home Office (Desde casa)
- Azure
- DevOps
- Capacitación
Postulación rápida

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GenAI Engineer

EPAM Systems, Inc. -
Desde casa

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Información del empleo

Beneficios

Vacaciones adicionales o permisos con goce de sueldo

Cualificaciones

Azure
Derecho
DevOps
NoSQL
Inglés
Experiencia en bases de datos
SQL
Redis
Kafka
Habilidades de comunicación
Python

Descripción completa del empleo

We are seeking a GenAI Engineer to lead the end-to-end development, deployment and operation of enterprise-grade AI-powered applications. The role combines backend engineering, LLM integration, cloud infrastructure and AI platform operations to deliver scalable GenAI solutions in production environments. You will work closely with AI/DS, Product and DevOps teams to build and scale AI-driven applications, ensuring reliability, observability, performance optimization and operational excellence across the full AI SDLC. The role also includes contributing to GenAI-assisted development practices, scaling enterprise AI SDLC processes, supporting AI Beauty Chat initiatives through agentic micro-pod delivery models and performing System Steward responsibilities across AI platform initiatives.

Responsibilities

Design, develop, deploy and maintain backend services for AI/LLM-powered applications
Own E2E delivery of GenAI features from implementation to production support
Integration and operation of LLM APIs (e.g. OpenAI) in enterprise production environments
Development of APIs, orchestration layers and microservices supporting agentic AI workflows
Optimization of LLM systems for latency, resiliency, retries, fallbacks and cost efficiency
Implementation of CI/CD pipelines, observability, monitoring and logging for AI services
Collaboration with AI/DS, Product, DevOps and platform teams to streamline delivery and improve reliability
Work with Azure cloud environments and distributed systems (Redis, Kafka, SQL/NoSQL)
Support for MCP integrations, agentic memory initiatives and AI orchestration frameworks
Drive GenAI-assisted development practices and scale AI SDLC processes
Contribution to AI Beauty Chat delivery through agentic micro-pod execution models
Execution of System Steward responsibilities in agentic micro-pods

Requirements

2+ years of Python backend engineering experience
Expertise in building and operating production-grade GenAI/LLM applications end-to-end
Hands-on experience with OpenAI or other LLM APIs in production
Proficiency in prompt engineering, agentic workflows and orchestration patterns
Capability to handle LLM operational challenges: latency, retries, fallbacks, observability and cost optimization
Strong understanding of scalable backend and distributed system architecture
Skills in CI/CD, DevOps workflows and Azure cloud environments
Background in applying GenAI across the SDLC (AI-assisted development, testing, deployment and delivery workflows)
Working knowledge of SQL/NoSQL databases, Redis and Kafka
Familiarity with Databricks and MCP
Excellent English communication skills (B2+ level)

We offer

International projects with top brands
Work with global teams of highly skilled, diverse peers
Healthcare benefits
Employee financial programs
Paid time off and sick leave
Upskilling, reskilling and certification courses
Unlimited access to the LinkedIn Learning library and 22,000+ courses
Global career opportunities
Volunteer and community involvement opportunities
EPAM Employee Groups
Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn

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devops engineer (observability) empleos

GenAI Engineer

Lead AI Forward Engineer

Head of Applications Architecture

Senior GenAI Engineer

Senior Azure Platform Engineer

Ingeniero Senior de Plataforma Azure

ML Engineer — Automation

Senior Middleware Engineer

Sr. Backend Engineer (Golang)

Software Development Engineer in Test (SDET)

Full-stack Lead/Senior Developer (C# + Angular)

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