Location: 100% Remote Role

Job Type: Full-Time

Target Salary Range*: $180,000 - $230,000.

• This represents the potential salary range for this position depending on education level, years of experience and/or certifications in addition to other position specific requirements which may impact salary

Position Overview

The Amatriot Group is seeking an AI Engineer to support a leading healthcare client. This role sits at the
intersection of artificial intelligence, machine learning, and cloud engineering, with a strong emphasis on
building and deploying GenAI and ML solutions within Google Cloud Platform (GCP) environments. The
ideal candidate brings a blend of software development, MLOps, and data engineering experience,
enabling them to design, develop, and operationalize scalable AI-driven applications. This is a highly
collaborative position supporting critical healthcare initiatives, where candidates will work across
engineering, data, and business teams to deliver production-ready AI solutions that drive innovation,
efficiency, and data-driven decision-making.

Required Skills

• Strong knowledge of programming languages like Python or Java or R
• Experience with AI frameworks such as TensorFlow or PyTorch.
• Experience in create and refine algorithms, neural networks, and other machine learning techniques.
• Experience in machine learning, deep learning, natural language processing (NLP), and computer vision.
• Experience in collect, analyze, and manage large datasets to train AI models.
• Experience in developing and deploying machine learning models.
• Need Machine/Deep Learning Experience in building models for time series modelling and predictive analytics using TensorFlow, PyTorch.
• Advanced Prompt Engineering Skills
• Experience in Agentic AI Frameworks and Workflow using any like Lang graph or CrewAI or Open AI Swarm
• Skilled with RAG Frameworks with model ReRankers and Tool Calling
• Expert in Python Programming.
• Desired – Prior Healthcare industry experience

Tech Stack

• GCP Fundamentals
  • Compute Services: Cloud Run, GKE (Google Kubernetes Engine), Vertex AI Workbench,
  • AI Notebooks.
  • Storage & Databases: BigQuery, Cloud Storage
  • Networking & Security: VPC, IAM (Identity and Access Management), Data Loss
  • Prevention (DLP).
  • Serverless & Event-Driven Architectures: Cloud Functions, Pub/Sub, Cloud Tasks.
• Machine Learning & Gen AI on GCP
  • Vertex AI: Managed AI/ML platform for training, deploying, and fine-tuning models.
  • Gemini API & Model Garden: Pre-trained Gen AI models (text, vision, multimodal).
  • TensorFlow & JAX: Model development and optimization.
  • TPUs & GPUs on GCP: Understanding specialized hardware for AI acceleration.
  • ML Pipelines: Using Kubeflow and TFX (TensorFlow Extended).

• Software Development & MLOps
  • Python & AI Frameworks: TensorFlow, PyTorch, Hugging Face.
  • API Development: REST & gRPC API design for AI integration.
  • Docker & Kubernetes: Containerizing and deploying AI solutions.
  • CI/CD & MLOps: Cloud Build, Vertex AI Pipelines, GitOps.

• Data Engineering & Processing
  • Data Pipelines: Using Apache Beam & Dataflow.
  • Big Data Processing: BigQuery ML, Dataproc (Spark, Hadoop).
  • Feature Engineering: AI Platform Feature Store