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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Forward Deployed Engineer, Enterprise Context Layer, Agentic Data Cloud - **Company:** Google LLC - **Location:** Sunnyvale, CA, United States - **Experience:** Experienced - **Salary:** $174,000 - $252,000 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Business Logic, Computer Vision, Bioinformatics, Cloud Computing, Graph Database, Statistical Hypothesis Testing, Open Source Technology, Software Engineering, Large Language Models, Multi-Agent Systems, Llamaindex, Generative AI, Agentic-AI, Model Context Protocol - **Published:** October 15, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3448935993&tx=KL4747FFL&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area. Share Forward Deployed Engineer, Enterprise Context Layer, Agentic Data Cloud, * Bachelor's degree or equivalent practical experience. * 5 years of experience in software development and testing or launching software products. * 3 years of experience with software design/architecture. * Experience with Generative AI (GenAI) concepts (e.g., Large Language Model (LLM), multi-modal, large vision models). Preferred qualifications: * Experience with Knowledge Graph, Ontologies. * Experience developing with Generative AI and Large Language Models. * Familiarity with open-source AI orchestration frameworks (e.g., LangChain, LlamaIndex). Experience with agentic architectures, tool usage, or the Model Context Protocol (MCP). * Background in automated evaluation and benchmarking pipelines * Ability to quickly understand customer needs in new domains, and form and test hypotheses on technical solutions and evaluations to improve model/agent outcomes to meet needs. ## Description * Analyze customer industries and profiles to translate business logic into functional AI agents. * Identify necessary agent skills and APIs, map decision trees, and build system guardrails to ensure accurate outputs. * Build custom skills or integrations to assist customers, and document successful processes for future standardization. * Tune AI agents by providing the appropriate voice, tools, and specific knowledge base required for specific brands. 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