Track Manager - Identity And Access Management, Service-Oriented Architecture

Job Summary

Job Summary : Advanced architectural and technical expertise across microservices, Kubernetes, Kafka, RabbitMQ, and secure cloud platforms such as GCP. It demonstrates proficiency in LLMs and Generative AI, including Gemini, Vertex AI, Lang Chain, and RAG pipelines, as well as mastery of data systems like PostgreSQL, Redis, and Pinecone. The content also details agent system design, security frameworks, and the orchestration of end-to-end GenAI solutions, emphasizing standards for LLM integration, multi-agent communication, and robust microservices-based architectures.
Job Description : Good knowledge of Artificial Intelligence Architecture.
Job Responsibilities : •Architect end-to-end AI/GenAI solutions, including RAG pipelines, multi-agent orchestration, and A2A communication •Define standards for LLM integration across platforms (Gemini, Vertex AI, OpenAI, Claude, Llama) •Design and oversee development of MCP servers and orchestrated agent ecosystems •Create microservices-based architectures with secure API gateways, rate-limiting, and observability •Partner with product, client, and security teams to ensure Responsible AI compliance •Drive continuous innovation in prompt engineering and orchestration frameworks •Optimize performance, cost, and compliance across GCP (Vertex AI) and hybrid deployments

Key Responsibilities

NA

Skill Requirements

Skill Requirement : Architectural Expertise: Microservices, Kubernetes, Kafka, RabbitMQ •LLMs & GenAI: Gemini, Vertex AI, Lang Chain, Lang Graph, Google ADK, RAG Pipelines, EasyRAG •Data Systems: PostgreSQL, Redis, FAISS, Milvus, Pinecone •Agent Systems: MCP Server design, A2A communication frameworks •Security: OAuth2, encryption, compliance frameworks •Cloud Platforms: GCP (Vertex AI, GKE, Cloud Run)

Other Requirements

NA