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Tier-1 brand, metro locations, mid-level generalist AI role, and broad skillset requirements increase applicant competition.
Role requires specialized LLM, agent-framework, and enterprise integration experience, limiting cross-industry transferability.
Mandatory 6+ years plus explicit LLM, Vertex/Gemini, cloud-native, and language requirements make filters stringent.
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Lead design and development of scalable, secure enterprise AI agent orchestration frameworks and integrations for agent lifecycle, workflows, and multi-agent collaboration.
Implement and optimize AI agent orchestration using Gemini, Vertex AI, and internal platforms with focus on performance, observability, safety, and governance.
Enable engineering teams via SDKs, reusable libraries, documentation, and direct technical support to build production-grade high-code AI agents.
6+ years software engineering experience, strong distributed systems and backend architecture background.
Proficient coding in Python plus at least one of: Go, Java, or TypeScript.
Hands-on production experience with LLM-based systems, prompt engineering, RAG, tool calling, agent frameworks, and enterprise AI platforms like Vertex AI or Gemini APIs.
Experience with cloud-native infrastructures (Docker, Kubernetes), API design, microservices, security patterns, and integration with orchestration frameworks (e.g., LangChain).
Experienced in building or integrating complex multi-agent or autonomous AI workflow orchestration systems in enterprise environments.
Strong backend engineering focus with emphasis on scalable, secure, and reusable code for AI systems and seamless enterprise platform integration.
Proven ability to drive adoption by supporting cross-functional engineering teams through SDK development, technical guidance, and comprehensive documentation.