What are the responsibilities and job description for the Senior GCP AI Cloud Engineer position at Logic Software Solutions?
Job Description: Senior GCP AI Cloud Engineer (Gen AI Vertex AI Focus)Location: USA (Hybrid - San Francisco Santa Clara)Experience:& 10 YearsStart Date:& ImmediatelyAbout the RoleWe are seeking a highly seasoned and hands-on& Senior GCP AI Cloud Engineer& to join our dynamic team. You will be at the forefront of designing, building, and scaling cutting-edge Generative AI solutions on the& Google Cloud Platform (GCP). This role requires deep expertise in the GCP AI/ML stack, especially& Vertex AI& and the& Gemini& model family, and a proven ability to translate complex product requirements into robust, production-grade systems. You will be a key player in driving our AI strategy and implementation on GCP.Key ResponsibilitiesGCP AI Solution Architecture Development:Design, build, and deploy sophisticated Generative AI applications on GCP, with a strong focus on& AI agents& and multi-step reasoning systems built within the& Vertex AI& ecosystem.Leverage and fine-tune foundational models, including the& Gemini& family (e.g., Gemini Pro, Gemini Ultra), using& Vertex AI& for model training, deployment, and management.Implement and orchestrate complex LLM workflows using& Vertex AI Agent Builder& and frameworks like& LangChain& on GCP for tasks such as Retrieval-Augmented Generation (RAG), summarization, and agentic behaviors.Architect and implement& RAG pipelines& on GCP, integrating& Vertex AI Search& and& Conversational AI& or custom solutions with vector databases.GCP Infrastructure Data Engineering:Architect and implement end-to-end AI solutions leveraging a wide array of GCP services.Integrate GCP services for& storage& (Cloud Storage, BigQuery),& serverless logic& (Cloud Functions, Cloud Run),& data processing& (Dataflow, Dataproc), and& messaging& (Pub/Sub) to create comprehensive, scalable AI pipelines.Build and maintain reliable and cost-effective data pipelines on GCP to support AI model training and inference.Rapid Prototyping Model Evaluation on Vertex AI:Use& Vertex AI Model Garden& and& Vertex AI Evaluation& to quickly conduct experiments, benchmark new LLM models, and analyze their performance, features, and cost.Implement MLOps practices using& Vertex AI Pipelines,& ML Metadata, and& Model Monitoring& to ensure model reliability and performance in production.Engineering Excellence Security on GCP:Employ& Infrastructure as Code (IaC)& using& Terraform& to provision and manage GCP resources in a repeatable and scalable manner.Implement robust security measures for AI systems using GCP’s& Identity and Access Management (IAM),& Cloud KMS& for encryption, and ensure compliance with data governance policies using& Data Loss Prevention (DLP)& and& VPC Service Controls.Champion software engineering best practices, including version control (Git), CI/CD using& Cloud Build, and MLOps principles.Collaboration Leadership:Work closely with Gen AI Leads and cross-functional team members to refine the product backlog, provide technical estimates, and deliver on sprint commitments.Mentor junior engineers and evangelize best practices in Gen AI development on GCP.Mandatory Technical Skills Experience (Primary)GCP AI/ML Gen AI Stack:Vertex AI Platform:& Deep, hands-on experience with the core services of& Vertex AI, including Model Training, Batch and Online Prediction, Feature Store, Pipelines, and Model Registry.Gemini Foundational Models:& Production-level experience integrating with the& Google Gemini& model family (especially Pro 1.x) via API endpoints and within the Vertex AI environment.LLM Frameworks Agents:& Thorough, implementation-level exposure to building& LLM agents& using& LangChain& and/or& Vertex AI Agent Builder. A deep understanding of agentic patterns and tools.Vector Databases:& Practical experience with vector databases like& Vertex AI Vector Search& (preferred), Pinecone, or Chroma for building semantic search systems.GCP Development Services:GCP Core Services:& Extensive hands-on experience with core GCP infrastructure and serverless services:& Cloud Storage, Cloud Functions, Cloud Run, IAM, BigQuery, and Pub/Sub.Programming:& Excellent programming skills and high proficiency in& Python& (primary) for Gen AI orchestration and scripting. Secondary proficiency in& PySpark& or& Java& is highly desirable.AI-Assisted Development:& A thorough understanding and practical use of AI-assisted development tools like& Cursor& for rapid prototyping and code generation.Secondary Desirable SkillsInfrastructure as Code:& Proficiency in& Terraform& for managing and automating GCP infrastructure.Multi-Cloud (AWS):& Experience with AWS AI/ML services (e.g., SageMaker, Bedrock) is a plus.Security Compliance:& Strong understanding of GCP security principles, specifically& IAM, Cloud KMS, and VPC Service Controls& for securing AI models and data.MLOps:& Familiarity with MLOps tools and practices on GCP for model versioning, monitoring, and lifecycle management.Personal AttributesSelf-Starter:& Ability to work autonomously in a remote setting, manage priorities, and take ownership of projects from conception to delivery.Innovative Problem Solver:& Passion for exploring new technologies and a knack for solving complex, ambiguous problems.Analytical Mindset:& Strong ability to analyze data, model outputs, and system performance to make informed decisions.Excellent Communicator:& Clear and concise communication skills, capable of collaborating effectively with both technical and non-technical stakeholders.Agile:& Comfortable working in a fast-paced, agile environment.What We OfferA remote-first work culture.Opportunity to work on cutting-edge GCP AI technologies and complex challenges.A collaborative and intellectually stimulating environment.Competitive compensation and benefits.