Application Developer - Cognitive Application Automation

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an Application Developer - Cognitive Application Automation in United States.

This role offers a unique opportunity to design, build, and automate cutting-edge machine learning workflows and pipelines in a cloud-first environment. You will work with advanced tools and technologies to deploy and manage LLM or RAG-based models, ensuring scalable, secure, and cost-efficient solutions. Collaborating closely with cross-functional teams, you will implement CI/CD pipelines, containerization, and orchestration strategies to optimize ML environments. This position provides exposure to the full lifecycle of machine learning operations, from development to production, while contributing to high-impact automation projects in a remote and fast-paced setting.

Accountabilities:

• Design, implement, and automate ML workflows and pipelines using AWS SageMaker, Lambda, Step Functions, ECS/EKS, and S3.
• Deploy, manage, and monitor LLM or RAG-based models using SageMaker JumpStart or custom endpoints.
• Implement CI/CD pipelines, containerization strategies, and orchestration frameworks for ML environments.
• Ensure solutions are scalable, secure, cost-efficient, and aligned with AWS best practices.
• Collaborate with teams to implement monitoring frameworks and manage feature stores/data versioning.
• Troubleshoot, optimize, and maintain ML environments to ensure reliability and performance.
• Document workflows, processes, and technical solutions to support reproducibility and team knowledge sharing.

• 10+ years of experience in Software Engineering, DevOps, or Data Platform Engineering, with at least 5+ years in MLOps.
• Strong expertise in AWS services: SageMaker Studio, Pipelines, Model Registry, Experiments, Model Monitor, Lambda, Step Functions, ECS/EKS, S3, Glue, CloudWatch, CodePipeline.
• Proficiency in Terraform or CloudFormation for Infrastructure as Code.
• Advanced Python, Bash, and Boto3 scripting skills.
• Experience with CI/CD, Docker, Kubernetes/EKS, and container orchestration.
• Hands-on experience deploying LLM or RAG models, managing feature stores, and implementing monitoring frameworks such as Prometheus, Grafana, or EvidentlyAI.
• AWS certifications preferred.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
• Excellent verbal and written communication skills, with the ability to interact professionally with diverse teams.