Google Cloud Platform AI Engineer /Technical Lead

Job Title: Google Cloud Platform AI Engineer / Hands-on Technical Lead (Client Architect Collaboration necessary)
Location: Hartford, CT/Remote working in EST Hours

The Google Cloud Platform AI Engineer / Hands-on Technical Lead partners closely with enterprise and solution architects to design, build, and deliver scalable AI/ML solutions on Google Cloud Platform. This role is both strategic and deeply hands-on, ensuring that architectural vision is translated into robust, production-grade implementations. The engineer leads the development of ML models, data pipelines, and MLOps frameworks while aligning designs with architectural standards, security guidelines, and best practices. The position also acts as a technical bridge between architecture teams, data science teams, and application engineering groups to ensure seamless integration of AI capabilities across the organization.

Key Responsibilities

• Collaborate with enterprise and solution architects to define AI/ML system architecture, reference patterns, and integration models on Google Cloud Platform.
• Translate architectural designs into hands-on implementation using Vertex AI, BigQuery, Dataflow, Pub/Sub, Cloud Run, and related Google Cloud Platform services.
• Lead end-to-end development of machine learning models, including data ingestion, feature engineering, training, validation, deployment, and monitoring.
• Build and maintain MLOps pipelines aligned with architectural standards (CI/CD, automated deployments, model governance).
• Provide technical expertise in choosing appropriate Google Cloud Platform services, ML frameworks, and design patterns.
• Champion cloud-native best practices in security, scalability, reliability, and cost optimization.
• Mentor and guide engineering and data science team members, ensuring consistent alignment with architectural direction.
• Conduct design reviews, code reviews, and contribute to architecture documentation and decision records.

Key Skills

• Strong hands-on expertise with Google Cloud Platform AI/ML ecosystem (Vertex AI, BigQuery, Dataflow, Cloud Storage, Pub/Sub, Cloud Run).
• Proficiency in Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn), and containerization (Docker, Kubernetes/GKE).
• Good understanding of cloud architecture, microservices, event-driven patterns, and data engineering pipelines.
• Experience building scalable, secure MLOps frameworks and CI/CD pipelines.
• Excellent communication and collaboration skills for working with architects, stakeholders, and cross-functional teams.