At Fujitsu, we've been driven to create a sustainable world through innovation since 1935. Today, we lead in digital transformation globally with our 130,000 employees across 50+ countries. We empower our diverse community to achieve greatness through career development and opportunities.

Company: Fujitsu

Role: System Architect- AI Developer

Location: Pune | Primary Location Only

Role Focus: • Design and develop enterprise-grade AI, GenAI, and intelligent automation solutions • Build AI-powered business applications using Azure AI Services, Azure OpenAI, Microsoft Copilot, and Agentic AI frameworks • Develop intelligent workflows integrating AI, automation, enterprise systems, and business processes • Design scalable and secure AI architectures integrating enterprise applications and cloud services • Create reusable AI components, frameworks, accelerators, and reference architectures • Lead development of Proof of Concepts (PoCs), MVPs, and production-grade AI solutions • Build Retrieval Augmented Generation (RAG) solutions using vector databases and enterprise knowledge sources • Design and develop AI Agents, Multi-Agent Systems, Autonomous Workflows, and Agentic AI solutions • Implement prompt engineering, prompt chaining, grounding techniques, and response optimization • Handle hallucination mitigation, response validation, guardrails, and responsible AI implementation • Evaluate and optimize LLM performance, latency, token consumption, and cost • Design AI orchestration workflows and multi-agent collaboration patterns • Build tool-enabled agents integrating enterprise systems and APIs • Integrate AI solutions enterprise solutions • Design, develop, and consume REST APIs and GraphQL APIs • Develop event-driven and real-time integrations • Implement secure authentication and authorization • Develop serverless and microservices-based AI architectures using Azure Functions, Logic Apps, and containerized services • Implement AI governance, compliance, security, and Responsible AI principles • Implement AI observability, monitoring, tracing, evaluation, and performance measurement • Build AI telemetry, usage analytics, feedback loops, and continuous improvement mechanisms • Perform AI validation testing, integration testing, and model evaluation • Ensure enterprise-grade security, scalability, availability, and maintainability • Maintain technical documentation, architecture diagrams, and solution artifacts