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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Innovation Software Engineer - Hybrid/Remote - **Company:** Genesis10 - **Location:** Columbus, OH, United States (Remote available) - **Experience:** Expert - **Salary:** $133,120.0 - $149,760.0 - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Software Applications, User Authentication, Microsoft Azure, Cloud Engineering, Continuous Integration, Design of User Interfaces, Python (Programming Language), Routing, OpenAI, Software Safety, Secure Coding, Software Deployment, Software Engineering, Systems Integration, TypeScript, Data Logging, Scripting, Google Cloud, Enterprise Software Applications, Spring Cloud, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Software Security, Generative AI, Amazon Virtual Private Cloud (VPC), Backend, Vertex AI Vector Search, Build Management, Containerization, AI Platforms, Information Technology, Google Gemini, Programming Languages - **Published:** October 27, 2026 - **Apply:** https://www.adzuna.com/details/5828399096 ## About the Role * Bachelor's degree in Computer Science, Information Technology, Engineering or a related technical field * 8+ years of experience in software engineering, application development, and end-to-end innovative solution delivery * Demonstrated hands-on software development experience building full-stack applications end-to-end such as APIs, back-end applications, and UIs * Strong hands-on Google Cloud development experience with demonstrated experience deploying applications or AI solutions within Google Cloud Platform * Production experience implementing AI-enabled applications using Vertex AI and Gemini; experience should extend beyond using Gemini or other GenAI tools solely as coding assistants * Hands-on experience building and deploying agentic or multi-agent solutions using frameworks such as Google ADK, Agent Engine, LangGraph, or comparable agent orchestration frameworks * Strong experience integrating models and AI services into production applications in a hands-on capacity * Experience deploying cloud-native applications and AI services, preferably using Google Cloud Run * Comfort working in a fast-paced environment, progressing despite ambiguity and ability to independently lead development workstreams from concept to execution * Clear, structured verbal and written communication skills; collaborative and proactive working style Desired Skills: * Strong full-stack experience across backend applications, APIs, integrations, and functional UI development * Experience designing or integrating with an AI gateway, LLM gateway, or model-proxy platform, including model routing, authentication, access controls, and guardrails * Experience implementing AI safety and security controls using Model Armor or comparable technologies * Experience managing token usage, model consumption, observability, and AI-related cost governance * Experience implementing grounding/RAG solutions using Vertex AI Search / Discovery Engine or comparable enterprise retrieval platforms * Strong hands-on development experience using modern programming languages and frameworks such as Java, Python, TypeScript/JavaScript, or similar * Experience with containerization, CI/CD, cloud-native deployment patterns, and operating applications within enterprise environments * Experience building automation solutions, including workflow engines, scripting, web automation, and system-to-system integrations * Experience deploying applications within regulated or highly controlled environments, including exposure to VPC Service Controls (VPC-SC), private networking, DLP, secure coding practices, and application security * Experience with AWS Bedrock, Azure OpenAI, or comparable AI platforms is beneficial when combined with demonstrated hands-on Google Cloud AI deployment experience * Proven track record of delivering innovative solutions using emerging technologies, with focus on rapid experimentation, production implementation, and measurable outcomes ## Description This role focuses on the high-velocity development of innovation solutions, with a strong emphasis on building and deploying AI-enabled and agentic applications within Google Cloud. The Senior Innovation Software Engineer will lead the development of applications, APIs, workflow automations, integrations, and agent-based solutions that demonstrate clear business value. This individual will partner closely across the Innovation team to develop end-to-end high-quality solutions using Vertex AI, Gemini, and modern agent frameworks while ensuring solutions are secure, testable, observable, and ready for broader reuse and production deployment., * Lead the development of prototypes, proof-of-concept solutions, and production-ready applications to validate new ideas and technologies, with emphasis on building working applications end-to-end * Design and implement APIs, backend services, workflow automations, UI experiences, and agent-based solutions to support innovation use cases * Build and deploy AI-enabled application capabilities using Google Cloud technologies, including Vertex AI and Gemini * Design and implement agentic and multi-agent workflows using frameworks such as Google ADK, Agent Engine, LangGraph, or equivalent technologies * Deploy and operate AI-enabled applications and agent services using Google Cloud deployment patterns, ideally including Cloud Run, CI/CD, environment configuration, monitoring, logging, and observability * Design or integrate with AI gateways and model-proxy layers supporting model routing, authentication, access controls, guardrails, and model governance * Implement grounding and Retrieval-Augmented Generation (RAG) solutions using Vertex AI Search / Discovery Engine or comparable enterprise retrieval and grounding technologies * Support AI governance, including token usage, model consumption, cost management, access controls, security guardrails, and responsible model usage * Experiment with, develop, and implement emerging technology solutions and translate them into working, scalable solutions * Develop and maintain rapid development patterns for innovation solutions, including starter kits, reusable components, internal demos, and implementation playbooks * Integrate solutions with enterprise systems as needed, including identity/access, data sources, eventing, internal services, and security controls, partnering with architecture and platform stakeholders * Evaluate emerging tools and frameworks that improve engineering velocity, AI orchestration, security, reliability, and quality * Operate with limited supervision, proactively defining tasks, making progress visible, and driving solutions from concept through deployment