> Markdown version of [/jobs/ext/3441640-gen-ai-engineer](https://www.wearedevelopers.com/jobs/ext/3441640-gen-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Gen AI Engineer - **Company:** J2B Global LLC - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, User Authentication, Python (Programming Language), Rapid Prototyping Process, Software Engineering, Unstructured Data, Chatbots, ReactJS, Large Language Models, Multi-Agent Systems, Information Technology, Data Pipelines, Programming Languages - **Published:** September 15, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=d138a759b1f3e26b ## About the Role qualifications Bachelor's degree in engineering, Computer Science, a related field, or equivalent practical experience. 5 years of experience with software development using Python or similar coding languages. Experience architecting AI systems on cloud platforms (e.g., GCP). Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions. Experience taking production-grade AI-driven solutions from conception to launch for customers. Experience leading technical discovery sessions with customers. Hands-on experience implementing and customizing Google's Conversational AI product suite, including Conversational Agents (Gemini-powered CX), Customer Engagement Suite (CES), and Contact Center AI (CCAI). Preferred qualifications Master's or PhD in AI, Computer Science, or a related technical field. Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation). Knowledge of "LLM-native" metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing. Additional deployment readiness criteria (Google RFI benchmark) Conversational AI & Agentic Depth: Production-grade experience architecting voice and agentic systems across the Google Enterprise CX ecosystem (Dialogflow CX, CX Agent Studio, SCRAPI, Agent Assist, CCaaS). Vetted Technical Rigor: Formally assessed, top-decile engineering talent (e.g., Google AI/FDE Bootcamp certification or verified 80%+ benchmark assessments). Telecom Architecture Fluency: Demonstrated domain depth with telecom APIs, user authentication (UA), and enterprise business architectures (BAA). Autonomous Delivery & Multiplier Impact: Senior "tiger team" talent capable of driving execution independently while actively upskilling co-delivery partner teams. ## Description future product roadmap. Job responsibilities Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable ROI. Architect and code the "connective tissue" between Google's AI products (Gemini-powered CX, Customer Engagement Suite, and Contact Center AI) and customer's live infrastructure, including APIs, legacy data silos, and security perimeters as part of an expert team. Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, and latency. Identify repeatable field patterns and friction points in Google's AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams. Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption. 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