[Remote] Forward Deployment Engineer (Architect Level) — Google Cloud Platform
Note: The job is a remote job and is open to candidates in USA. Dice is seeking a Forward Deployment Engineer for Google Cloud Platform, who will work closely with enterprise customers to design and deliver AI solutions. The role requires expertise in AI engineering and Python programming to create production-grade systems that address customer needs swiftly and effectively.
Responsibilities
- Embed with enterprise customers to scope, architect, and deliver end-to-end AI solutions on Google Cloud — from data layer through front-end interface
- Design and build agentic AI systems using Gemini, the Google Agent Development Kit (ADK), and LangChain — including multi-agent orchestration, tool use, memory, and grounding
- Write expert-level Python to develop, train, evaluate, and deploy ML models and AI pipelines on Vertex AI
- Prototype rapidly — solve customer-blocking technical scenarios (e.g., building a custom audio connector or data integration) within hours when required
- Build full-stack solutions spanning BigQuery, Cloud Run, Cloud Functions, Pub/Sub, Apigee, and Vertex AI to deliver integrated, production-ready systems
- Lead technical discovery sessions to identify high-value AI use cases, assess data readiness, and define measurable success criteria with customers
- Implement MLOps best practices on Vertex AI: automated pipelines, model monitoring, feature stores, and CI/CD for ML workflows
- Leverage Google AI services — Document AI, Speech-to-Text, Vision AI, Translation AI — for rapid capability delivery where custom models are not required
- Advise customers on responsible AI, model explainability, and AI governance using Google Cloud's built-in tooling
- Feed customer insights back to Fusion's engineering and product teams to shape our Google Cloud Platform AI practice
- Produce clear architecture diagrams, technical runbooks, and handoff documentation for every engagement
- Travel to customer sites as needed (typically up to 30%)
Skills
- Expert-level Python coding ability, including software design patterns, performance optimization, testing, and production-grade code quality
- Hands-on experience building agents using Gemini, Google ADK, and/or LangChain — including tool use, agent memory, multi-agent workflows, and RAG pipelines
- Demonstrated ability to solve ambiguous, blocking customer scenarios quickly — building working prototypes (e.g., audio connectors, API integrations, data pipelines) in hours
- Experience delivering end-to-end solutions across the stack, from data ingestion and model inference through APIs and user-facing interfaces
- 5+ years of professional software engineering experience, with at least 1 year deploying AI/ML solutions on Google Cloud Platform or equivalent cloud platform
- Hands-on experience with Vertex AI: training jobs, model endpoints, Pipelines, Feature Store, and/or Model Monitoring
- Strong understanding of Google Cloud Platform data services: BigQuery, Dataflow, Pub/Sub, and Cloud Storage
- Familiarity with Google Cloud Platform infrastructure fundamentals: IAM, VPC, Cloud Run, Cloud Functions, and Cloud Logging
- Excellent communication skills — able to present complex AI system behavior and trade-offs to both technical teams and executive stakeholders
- Google Cloud Professional Machine Learning Engineer or Professional Cloud Architect certification
- Experience with Gemini multimodal capabilities — vision, audio, and document understanding
- Background in NLP, computer vision, conversational AI, or time-series forecasting in a production setting
- Familiarity with additional agentic frameworks: CrewAI, AutoGen, or Google's Vertex AI Agent Builder
- Experience with Looker, Looker Studio, or data visualization for AI-driven analytics products
- Prior customer-facing experience in an applied AI or ML engineering role (e.g., Google PSO, ML consulting, or AI professional services)
- Knowledge of responsible AI practices: fairness metrics, model explainability (SHAP, LIME), and AI governance frameworks
Company Overview
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