19 publicaciones de empleo destacadas en sr. aws solutions architect (¡Están contratando!)

Applied AI Engineer (Automation)
Fusemachines —Desde casa
- Tiempo completo
- Home Office (Desde casa)
- Azure
- Administración de personal
- Doctorado
Lead .NET Full Stack Engineer (React)
EPAM Systems, Inc. —Desde casa
- Home Office (Desde casa)
- Azure
- Inglés
- Experiencia en bases de datos
- Plan de adquisición de acciones empresariales
Senior Database Engineer
EPAM Systems, Inc. —Desde casa
- Home Office (Desde casa)
- Azure
- Oracle
- Administración de personal
- Vacaciones adicionales o permisos con goce de sueldo
8d
Lead AI Forward Engineer
Thomson Reuters —Ciudad de México, CDMX
- Tiempo completo
- Azure
- DevOps
- Python
Senior Solution Engineer - SI Partners - MX
Snowflake —Desde casa
- Home Office (Desde casa)
- Azure
- Doctorado
- Informática
Sr Procurement Project Spec
Honeywell —Monterrey, N. L.
- Tiempo completo
- Azure
- Informática
- Experiencia en bases de datos
6d
Senior AI Engineer (Content Intelligence Applications)
EPAM Systems, Inc. —Desde casa
- Home Office (Desde casa)
- Azure
- Informática
- Inglés
- Vacaciones adicionales o permisos con goce de sueldo
Senior Database Reliability Engineer
Sezzle —Desde casa
- Tiempo completo
- Home Office (Desde casa)
- Administración de personal
- Informática
- DevOps
Senior/Lead AI Engineer
EPAM Systems, Inc. —Desde casa
- Home Office (Desde casa)
- Azure
- ERP systems
- Inglés
- Plan de adquisición de acciones empresariales
1d
Senior AI Engineer in Content Intelligence Applications
EPAM Systems, Inc. —Desde casa
- Home Office (Desde casa)
- Azure
- Informática
- Inglés
- Vacaciones adicionales o permisos con goce de sueldo
Senior Data Engineer - Snowflake & Databricks
EPAM Systems, Inc. —Desde casa
- Home Office (Desde casa)
- Azure
- Inglés
- SQL
14d
Lead Python Engineer with Cloud experience
EPAM Systems, Inc. —Desde casa
- Home Office (Desde casa)
- Azure
- Administración de personal
- DevOps
- Plan de adquisición de acciones empresariales
Senior Python Developer
Endava —Monterrey, N. L.
- Tiempo completo
- Trabajo híbrido
- Azure
- Oracle
- Administración de personal
- Programa de referidos
Postulación rápida
Data Consultant - Snowflake & Databricks
EPAM Systems, Inc. —Desde casa
- Home Office (Desde casa)
- Azure
- Inglés
- SQL
13d
SR Software Engineer (Data focus) - (Remote, LATAM)
ITX Corp —Monterrey, N. L.
- Tiempo completo
- Home Office (Desde casa)
- Bilingüe
- Azure
- Inglés
Postulación rápida
14d
Solutions Architect
SunnyData —México
- Tiempo completo
- Home Office (Desde casa)
- Azure
- Administración de personal
- Informática
Sr. QA Automation Engineer
Grid Dynamics —México
- Tiempo completo
- Home Office (Desde casa)
- DevOps
- Java
- JavaScript
- Seguro de la vista
- Seguro de vida
Senior Systems Analyst
Enroute —México
- Tiempo completo
- Home Office (Desde casa)
- Microsoft Excel
- Administración de personal
- Análisis de datos
- Seguro de vida
Postulación rápida
Senior GenAI Data Engineer (Databricks)
Enroute —México
- Tiempo completo
- Home Office (Desde casa)
- Salesforce
- DevOps
- Inglés
- Seguro de vida
Postulación rápida
10d

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Applied AI Engineer (Automation)

Fusemachines -
Desde casa

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Información del empleo

Tiempo completo

Cualificaciones

Elasticsearch
Azure
Administración de personal
Derecho
Doctorado
Tooling
Google Cloud Platform
Herramientas de automatización
Experiencia en bases de datos
Docker
Redis
Kafka
Gestión de venta al por menor
Bases de datos orientadas a grafos
Python

Descripción completa del empleo

About Fusemachines

Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic) and more than 450 full-time employees, Fusemachines brings global AI expertise to transform companies worldwide. Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government.

Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.

Type: Remote, Full-time

Role Overview

As an Applied AI Engineer(Automation), you will deliver high-impact AI and automation solutions for clients—owning work from requirements discovery through prototype and production deployment. You’ll build reliable, maintainable systems that integrate LLMs into real business workflows via APIs, automation platforms, and backend services.

This is a mid-to-senior individual contributor role. You’ll collaborate closely with Solutions Architects, Delivery/Engagement leads, and Product Managers to scope, build, ship, and iterate on client solutions.

Key Responsibilities

Design & Deploy: Design, develop, and deploy tailored AI and automation solutions aligned to client objectives.
Build Workflows & Services: Translate business problems into production-grade AI workflows and services using Python, automation tools (n8n/Make/Zapier or similar), and LLM platforms/APIs (e.g., OpenAI, IBM watsonx.ai, Amazon Bedrock), plus retrieval systems.
Agentic Systems: Build and deploy agentic workflows using LangChain, LangGraph, and Google ADK, including tool calling and structured outputs.
Retrieval & Knowledge Systems: Implement RAG pipelines using vector databases and search technologies (e.g., Pinecone, Elasticsearch, pgvector) and graph databases when appropriate.
Production: Ship fast prototypes, then harden them into scalable systems (testing, reliability, deployment, monitoring) independently or with a team.
Client Partnership: Participate in discovery, run technical calls/demos when needed, and communicate tradeoffs clearly to client and internal stakeholders.
Ongoing Support & Iteration: Improve deployed solutions through feature work, bug fixes, monitoring, prompt/model improvements, and additional automations.
Documentation: Produce clear technical documentation, client demos, and internal playbooks to enable reuse and scalability.
Continuous Learning: Stay current on LLM tooling and delivery best practices to improve quality and speed.

Success in This Role Looks Like

Solutions consistently meet or exceed client expectations and show measurable impact (time saved, cost reduced, improved conversion/deflection, faster cycle time).
Clients trust you as a go-to engineering partner and expand usage of deployed AI workflows.
Deliveries are production-ready: monitored, testable, documented, and maintainable.

Required Qualifications

3–8 years of software or AI engineering experience (mid-to-senior).
2–3+ years of AI Automation, Generative AI, or Agentic AI (mid-to-senior).
Strong Python engineering skills and experience building APIs/services (e.g., FastAPI).
Hands-on experience integrating LLMs (e.g., OpenAI APIs or equivalents), including prompt design, structured outputs, and basic evaluation practices.
Experience with at least one workflow automation platform (n8n, Make, Zapier, or similar) and building reliable integrations.
Familiarity with RAG fundamentals and retrieval systems (embeddings, vector search); exposure to vector databases and/or Elasticsearch.
Production engineering fundamentals: Docker, cloud deployment (AWS/GCP/Azure/IBM), and experience with async/queuing patterns (e.g., Celery, Redis, Kafka).
Comfort operating in a client-facing environment: technical calls, demos, and collaborating with cross-functional stakeholders.

Preferred Qualifications

Experience with fine-tuning LLMs or other ML models; broader ML exposure is a plus (not required).
Familiarity with observability and tracing (e.g., LangSmith, OpenTelemetry) and prompt/version lifecycle management.
Experience with graph databases / knowledge graphs.
Familiarity with data governance and AI governance concepts (PII handling, auditability, access controls, risk awareness).
Prior consulting experience or work in fast-paced startup environments.

Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.

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