B2/C1 - AI Platform Engineer 2

GenAI Platforms AI/ML engineering ML Frameworks bigquery performance optimization Python MLOps tools Google Cloud Platform (GCP)

We are seeking a AI Engineer to design, build, and scale AI/ML solutions with a focus on enterprise-grade generative AI deployments. This role requires hands-on experience delivering customer-facing AI solutions on Google Cloud Platform, including direct experience with Gemini Enterprise., * Design, develop, and deploy AI/ML solutions and generative AI applications for enterprise customers

• Architect and implement solutions leveraging Gemini Enterprise (Gemini for Google Workspace / Gemini Enterprise AI agents, grounding, and search)
• Build and productionize ML pipelines, APIs, and services using Python
• Design and implement RAG (Retrieval-Augmented Generation) architectures, agentic workflows, and LLM-based applications
• Deploy, monitor, and optimize models and services on GCP (Vertex AI, BigQuery, Cloud Run, GKE, Cloud Functions, Pub/Sub)
• Collaborate with customers/stakeholders to gather requirements and translate business problems into scalable AI solutions
• Ensure solutions meet enterprise standards for security, scalability, performance, and cost efficiency
• Partner with data engineering, MLOps, and platform teams to integrate AI capabilities into existing systems
• Stay current with evolving GCP AI/ML offerings (Vertex AI, Gemini models, Agent Builder, Model Garden) and recommend adoption where relevant
• Mentor junior engineers and contribute to best practices for AI/ML development

• 7+ years of experience in software/AI/ML engineering roles
• Hands-on customer-facing experience with Gemini Enterprise (or equivalent enterprise GenAI platforms)
• Strong expertise in Google Cloud Platform (GCP) - Vertex AI, BigQuery, Cloud Run/GKE, IAM, networking basics
• Advanced proficiency in Python (ML libraries: TensorFlow, PyTorch, scikit-learn, LangChain/LangGraph, etc.)
• Solid understanding of LLM fundamentals: prompt engineering, fine-tuning, embeddings, vector databases, RAG
• Experience deploying and scaling ML models in production environments
• Strong understanding of API design, microservices, and cloud-native architecture
• Excellent communication skills - able to engage directly with enterprise customers and stakeholders, * GCP Professional certifications (Machine Learning Engineer, Cloud Architect, or Data Engineer)
• Experience with MLOps tooling (Vertex AI Pipelines, Kubeflow, MLflow)
• Experience with agentic AI frameworks and multi-agent orchestration
• Background in enterprise sales engineering, solutions architecture, or pre-sales technical consulting
• Familiarity with data governance, security, and compliance in AI/ML systems

The pay range that the employer in good faith reasonably expects to pay for this position is $36.98/hour - $57.79/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.