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AI Infrastructure Architect
Accenture(Other)
Job Publish Date: 19 hours ago
Bengaluru, IndiaFull Time7 - 9 YearsWork From OfficeSource : Foundit
Job Description
Project Role : AI Infrastructure Architect
Project Role Description : Architect and build custom Artificial Intelligence (AI) infrastructure/hardware solutions. Optimize AI infrastructure/hardware performance, power consumption, cost and scalability of computational stack. Advise on AI infrastructure technology and vendor evaluation, selection and full stack integration.
Must have skills : Microsoft Azure OpenAI Service
Good to have skills : NA
Minimum 7.5 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
Summary:
We are seeking a highly skilled Senior Agentic AI Developer to design, architect, and deliver next-generation intelligent agent solutions powered by Large Language Models (LLMs). The ideal candidate will bring deep hands-on expertise in building agentic AI systems using LangChain and LangGraph, and deploying scalable, enterprise-grade solutions leveraging Azure OpenAI (GPT-5.0 and above). This role focuses on developing autonomous, reasoning-driven AI agents capable of solving complex business problems, orchestrating workflows, and driving intelligent automation at scale.
Key Roles and Responsibilities:
Design multi-agent systems with capabilities like reasoning, planning, memory, and tool orchestration.
Define scalable architectures for distributed agents aligned with enterprise needs and cloud best practices.
Translate business problems into AI-driven workflows and agent-based solutions.
Develop stateful, multi-step agent workflows leveraging LangGraph constructs such as nodes, edges, and shared state.
Implement RAG (Retrieval-Augmented Generation), tool integrations, and external API orchestration.
Create reusable agent components, prompt templates, and orchestration pipelines.
Optimize performance, latency, cost, and response quality of LLM-based systems.
Implement memory management (short-term, long-term, vector-based).
Deploy solutions on Azure cloud, ensuring scalability, security, and reliability.
Work with DevOps teams for CI/CD pipelines, monitoring, and observability.
Implement guardrails, validation layers, and safe AI practices.
Participate in design reviews and risk assessments.
Mentor junior developers and contribute to best practices and reusable frameworks.
Drive innovation through POCs, accelerators, and reusable assets.
Required Skills & Experience:
Core Technical Skills
Strong hands-on experience with:
Experience with:
Cloud & DevOps
Hands-on experience with:
Project Role Description : Architect and build custom Artificial Intelligence (AI) infrastructure/hardware solutions. Optimize AI infrastructure/hardware performance, power consumption, cost and scalability of computational stack. Advise on AI infrastructure technology and vendor evaluation, selection and full stack integration.
Must have skills : Microsoft Azure OpenAI Service
Good to have skills : NA
Minimum 7.5 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
Summary:
We are seeking a highly skilled Senior Agentic AI Developer to design, architect, and deliver next-generation intelligent agent solutions powered by Large Language Models (LLMs). The ideal candidate will bring deep hands-on expertise in building agentic AI systems using LangChain and LangGraph, and deploying scalable, enterprise-grade solutions leveraging Azure OpenAI (GPT-5.0 and above). This role focuses on developing autonomous, reasoning-driven AI agents capable of solving complex business problems, orchestrating workflows, and driving intelligent automation at scale.
Key Roles and Responsibilities:
- Solution Architecture & Design
Design multi-agent systems with capabilities like reasoning, planning, memory, and tool orchestration.
Define scalable architectures for distributed agents aligned with enterprise needs and cloud best practices.
Translate business problems into AI-driven workflows and agent-based solutions.
- Development & Implementation
Develop stateful, multi-step agent workflows leveraging LangGraph constructs such as nodes, edges, and shared state.
Implement RAG (Retrieval-Augmented Generation), tool integrations, and external API orchestration.
Create reusable agent components, prompt templates, and orchestration pipelines.
- LLM & Agent Optimization
Optimize performance, latency, cost, and response quality of LLM-based systems.
Implement memory management (short-term, long-term, vector-based).
- Enterprise Integration & Deployment
Deploy solutions on Azure cloud, ensuring scalability, security, and reliability.
Work with DevOps teams for CI/CD pipelines, monitoring, and observability.
- Governance, Security & Responsible AI
Implement guardrails, validation layers, and safe AI practices.
Participate in design reviews and risk assessments.
- Collaboration & Leadership
Mentor junior developers and contribute to best practices and reusable frameworks.
Drive innovation through POCs, accelerators, and reusable assets.
Required Skills & Experience:
Core Technical Skills
Strong hands-on experience with:
- LangChain & LangGraph for agent orchestration
- Azure OpenAI (GPT-5.0 or higher) and LLM-based application development
- Agentic AI concepts: reasoning, planning, autonomy, tool usage
- Multi-agent systems and orchestration
- Python (must-have)
- API development (FastAPI/REST)
- Data integration and pipelines
Experience with:
- Prompt engineering and few-shot learning
- RAG pipelines, embeddings, and vector databases
- Knowledge graphs and contextual AI systems
Cloud & DevOps
Hands-on experience with:
- Azure AI services, Azure OpenAI, AI Foundry
- CI/CD pipelines, containerization (Docker/Kubernetes preferred)
- Monitoring tools (App Insights, Log Analytics)
- The candidate should have minimum 7.5 years of experience in Microsoft Azure OpenAI Service.
- This position is based at multiple locations.
- A 15 years full time education is required.
Key Skills
Api DevelopmentApp InsightsAzure AI servicesAzure OpenAI AI FoundryAzure OpenAI GPT-5.0 or higherCI CD pipelinescontainerizationcontextual AI systemsData integration and pipelinesDockerembeddingsFastAPIfew-shot learningKnowledge graphsKubernetesLangChainLangGraphLog AnalyticsMonitoring ToolsPrompt engineeringPythonRAG pipelinesRESTvector databases
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