Sr. Full Stack Software Engineer – AI Agents

Accountabilities:: Design multi-agent architectures, defining agent roles, responsibilities, delegation patterns, tool boundaries, and session and state management. Develop and deploy AI agents using Google's Agent Development Kit (ADK), including sequential, parallel, and loop workflows. Build agent tools and integrations that connect with customer and third-party systems through REST APIs and the Model Context Protocol (MCP). Develop full-stack applications, including modern web interfaces, backend services, and APIs that make agent capabilities accessible to end users. Build frontend experiences using TypeScript and modern component frameworks, supporting agent interactions, streaming responses, and authenticated user sessions. Design backend services and relational databases, including PostgreSQL schemas and version-controlled database migrations. Implement secure authentication and authorization for applications and agent tool calls using OAuth 2.0, OpenID Connect (OIDC), and JSON Web Tokens (JWT). Deploy and operate agents and application services on Google Cloud Platform using Cloud Run and Agent Engine, supporting managed environments and release processes. Integrate Gemini models through Vertex AI, implementing prompt design, function calling, and structured output. Develop and maintain agent evaluation suites, automated scoring, tracing, and feedback loops to measure quality, identify regressions, and improve prompts, tools, and agent architecture. Instrument agents and services with logging and observability capabilities to support production monitoring, troubleshooting, and debugging. Use Claude and other AI coding assistants to accelerate architecture, implementation, test generation, and code reviews, including coordinating multiple agents concurrently while validating all generated outputs. Establish automated testing and CI/CD practices across the stack, including unit, integration, frontend, end-to-end, and agent behavior regression tests. Participate in code reviews and document system architecture, technical decisions, and operational procedures for internal teams and customer stakeholders. Requirements: Bachelor's degree in Computer Science or equivalent practical experience. Professional full-stack software engineering experience, including delivering and operating production applications on Google Cloud Platform. Hands-on experience building and deploying AI agents using Google's Agent Development Kit (ADK). Strong knowledge of ADK agent definitions, tool design, session management, and state handling. Experience designing multi-agent systems, including agent delegation, sequential and parallel execution, loop workflows, and clearly defined context and responsibilities. Demonstrated experience building agent quality feedback loops, including evaluation datasets, automated output scoring, tracing, and iterative improvements to prompts, tools, and agent structures. Frontend development experience with TypeScript and a modern component framework, including REST API integration, streaming responses, and authenticated sessions. Backend service and API development experience, with knowledge of relational database design, particularly PostgreSQL, and versioned schema migrations. Strong understanding of web application authentication and authorization using OAuth 2.0, OIDC, and JWT. Experience deploying and operating agents and application services on GCP, particularly Cloud Run and Agent Engine. Practical experience with Gemini models on Vertex AI, including prompt engineering, function calling, and structured output. Experience integrating agent tools and external systems through MCP and REST APIs. Daily experience using Claude or other AI coding assistants for software design, implementation, testing, and review, including managing multiple AI agents concurrently. Strong engineering judgment and the ability to verify, troubleshoot, and correct AI-generated code and outputs. Experience implementing automated testing and CI/CD pipelines across frontend, backend, and agent workflows. Strong problem-solving, communication, collaboration, and documentation skills, with the ability to work effectively alongside technical leads, engineers, and customer stakeholders. Familiarity with the Agent-to-Agent (A2A) protocol. Experience with retrieval and grounding solutions, such as Vertex AI Search or vector search. Knowledge of observability tools and frameworks, including Cloud Trace, Cloud Logging, and OpenTelemetry. Experience with Google Cloud services such as Pub/Sub, Memorystore, and BigQuery. Experience integrating AI agents with Gemini Enterprise. Google Cloud Professional certifications. Benefits: Full-time employment. Remote work opportunity for candidates located in the United States. Opportunity to work on production-grade multi-agent AI systems using Google Cloud technologies and modern AI development tools. Collaboration with technical leaders, engineering teams, and customer stakeholders on complex AI-powered applications. Professional growth through hands-on work with emerging agent architectures, cloud infrastructure, and AI-assisted engineering practices.