Description

Design and deploy AI/ML and agentic AI solutions for automation and decisioning. You will own end-to-end ML pipelines, from training and deployment to production monitoring and optimization.

This role is on-site.

Responsibilities

• Build and maintain scalable ML pipelines for training, deployment, and monitoring using GCP services like Vertex AI, BigQuery ML, and Dataflow.
• Develop and integrate agent-based or multi-step AI workflows with enterprise applications.
• Implement MLOps practices including CI/CD, versioning, governance, and continuous model optimization.
• Collaborate with architecture teams to align AI solutions with platform design and ensure reliability.
• Construct scalable data pipelines supporting both batch and real-time processing.

Required Skills

• 6+ years of experience in AI/ML, data engineering, or cloud engineering.
• Strong programming skills in Python.
• Hands-on experience with ML frameworks: TensorFlow, PyTorch, Scikit-learn.
• Proficiency with GCP AI/ML services: Vertex AI, BigQuery ML, Dataflow.
• Experience with agentic AI, GenAI, and LLM-based workflows (multi-step reasoning, orchestration).
• Experience building and deploying ML pipelines in production.
• Knowledge of microservices architecture and API integration.
• Experience with containerization (Docker, Kubernetes) and CI/CD tools.
• Bachelor's degree in a relevant field.

Preferred Skills

• Experience implementing RAG, prompt orchestration, and AI workflow automation.
• Knowledge of Revenue Cycle Management financial systems.
• Relevant cloud or ML certifications.

Key Skills

Education

Bachelor's degree