Responsibilities
- Design and implement scalable, secure, production-grade pipelines for deploying and integrating agentic AI models.
- Build and maintain GCP or AWS cloud infrastructure across the AI lifecycle.
- Develop automated CI/CD and continuous training workflows for agentic AI models.
- Implement monitoring for model performance, health, decision-making accuracy, drift, latency, and bias.
- Integrate security, privacy, ethical AI safeguards, and regulatory compliance throughout the MLOps lifecycle.
- Collaborate with AI researchers, data scientists, software engineers, and product teams.
- Establish and enforce data and model governance frameworks covering quality, security, and compliance.
Requirements
- At least four years of experience in MLOps, DevOps, or a related field, including at least one year deploying and managing AI/ML models in production.
- At least four years of hands-on experience with Google Cloud Platform or Amazon Web Services.
- Experience with agentic or autonomous AI systems is highly preferred.
- Knowledge of Vertex AI, Cloud Storage, BigQuery, Cloud Functions, Amazon SageMaker, S3, Redshift, or Lambda.
- Strong knowledge of PyTorch, Langraph, CrewAI, and N8N, with proficiency in Docker and Kubernetes.
- Expertise in Python and familiarity with Bash and Terraform for automation.
- Strong experience with Git and version control systems.
- Hands-on experience with Lantrace, AgentOps, Prometheus, CloudWatch, or Grafana for production monitoring.
- Understanding of cloud and MLOps security principles, including IAM, data encryption, and secure pipeline design.
- Understanding of ethical AI principles such as bias detection, explainability, and regulatory compliance.
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field; advanced degrees or certifications in MLOps, AI/ML, or cloud technologies are valued.
- Strong interpersonal and communication skills for cross-functional collaboration and explaining technical concepts to diverse stakeholders.
Benefits
- 100% remote work.
- Contractor position for candidates in Latin America.
- East/West Coast time-zone coverage is required.
- Holidays off.
- Paid time off.
- Health insurance assistance program.
- Training provided.
Tech Stack
Categories
About CodeRoad
At CodeRoad, we accelerate ROI through end-to-end software engineering and technology execution. Our Velocity-as-a-Service (VaaS) delivery engine deploys elite nearshore delivery pods and AI-ready systems that execute your technology roadmap, deliver measurable outcomes, and scale innovation with certainty. Founded in 2002, CodeRoad pioneered nearshore engineering delivery from La Paz, Bolivia. Over two decades, we have expanded across Latin America to build a curated network of senior engineers, product leaders, and AI specialists who collaborate in real time with North American technology teams. Through senior-led delivery pods and mature engineering frameworks, we help organizations move from strategy to execution—turning complex technology initiatives into production-ready systems without the delays that slow innovation. Our teams support companies across industries including retail, automotive, transportation and logistics, food and beverage, financial services, and energy. We operate across the modern technology landscape, mastering languages, frameworks, cloud platforms, and AI-enabled development environments to support next-generation digital systems. With Velocity-as-a-Service, organizations gain the execution architecture needed to launch products faster, modernize platforms, and drive digital transformation with measurable ROI. CodeRoad gets you there — at full velocity.