Location
Remote (Colombia, Uruguay)
Seniority
Middle · 4+ years exp
Employment
Full-Time
Confirmed on the employer's own hiring board on Oct 29, 2026. First seen by Alion on Oct 29, 2026.
Overview
Company
Impact
Profile match
DataArt is a global software engineering and consulting firm headquartered in New York that builds and modernises custom software, data platforms and cloud infrastructure for clients in finance, travel, healthcare, media and retail. Founded in 1997, it runs delivery centres across Europe, the Americas and Asia, including offices in Wroclaw, Lublin and Lodz in Poland and teams in India, and works with more than 400 enterprise clients. Its openings include senior .NET, Java, Python and frontend engineers, DevOps and site reliability engineers, data architects and data engineers, QA automation leads and solution consultants.
We are looking for a hands on MLE and AI Ops Engineer to design, deploy, and operate data and AI products end to end. You will focus on platform and operations work, including infrastructure, MLOps pipelines, observability, security, and cost management.
The Passenger Experience Platform supports smarter and more reliable customer and commercial experiences through data and AI solutions. The team builds and serves ML and GenAI solutions on Google Cloud Platform using a containerized and infrastructure as code foundation, with AI assisted development as part of the daily workflow.
- Design, deploy, and operate ML and GenAI services end to end
- Build and maintain MLOps pipelines and CI/CD standards for data and AI workloads
- Enable the Data and AI platform to be reliable, scalable, and consumable across business domains
- Own environment and product infrastructure using Terraform on Google Cloud Platform
- Instrument observability and monitoring for models, pipelines, and services
- Apply security, IAM, governance, and cost optimization practices across data and AI
- Use AI assisted development to accelerate and improve delivery
- 4 plus years of experience in MLE, ML platform engineering, AI Ops engineering, or a closely related role
- Strong Python skills for services and data work using Pandas and FastAPI
- Hands on experience with MLOps across model deployment, model registry, serving, and monitoring
- Experience with GenAI engineering using LangChain, agents, MCP, vector databases, and response caching
- Experience with containerization and orchestration using Docker and Kubernetes
- Experience with infrastructure as code using Terraform and CI/CD pipelines for data and AI
- Cloud experience on Google Cloud Platform with BigQuery for analytical workloads
- Fluency in Spanish and intermediate English for documentation and international collaboration
- Experience with observability tooling such as Prometheus, Grafana, or Datadog
- Knowledge of data platform fundamentals including pipeline orchestration, lakehouse or warehouse concepts, and SQL transformations
- Knowledge of security, IAM, and data governance practices
- Strong critical thinking, communication, and collaboration in cross functional teams
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