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Accenture

Advises businesses and runs their technology

Large Language Model Architect

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree or equivalent in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology, or a related engineering discipline.
  • At least 10 years of experience in software engineering, data engineering, AI/ML engineering, or technology architecture.
  • At least 5 years of experience designing and deploying enterprise-grade advanced AI or cloud data solutions using at least one cloud vendor.
  • At least 2 years of experience in agentic AI, LLM, and generative AI solution architecture or engineering delivery.
  • At least 4 years of coding experience using Python, with experience in APIs, distributed systems, reusable frameworks, and cloud-native application patterns.
  • At least 4 years of experience in machine learning, deep learning, natural language processing, data engineering, analytical engineering, or AI product delivery.
  • Demonstrated experience as a solution or technology architect in an industry context such as banking, insurance, healthcare, public sector, retail, or energy.
  • Hands-on architecture and engineering experience with Microsoft Foundry / Azure AI Foundry, Foundry Agent Service, Azure OpenAI models, Azure AI Search, Prompt Flow, Azure Functions, Logic Apps, API Management, Event Grid, Microsoft Fabric, Entra ID, Key Vault, Azure Monitor, and Application Insights.
  • Strong knowledge of LLM architecture patterns, including RAG, embeddings, vector databases, prompt engineering, model routing, fine-tuning or adaptation, function calling, tool integration, and agent orchestration.
  • Ability to define enterprise AI platform patterns for performance, scalability, security, reliability, observability, governance, cost optimization, and operational support.
  • Experience designing reusable agent services, memory services, API gateways, integration adapters, orchestration layers, evaluation harnesses, and deployment pipelines.
  • Experience with CI/CD, infrastructure as code, automated testing, model evaluation, MLOps/LLMOps, monitoring, and production release governance.
  • Strong stakeholder management skills and ability to communicate architecture trade-offs, risks, and recommendations to engineering, product, security, and leadership teams.

Responsibilities

  • Translate business strategy and product goals into a technical vision, architecture blueprint, non-functional requirements, and implementation roadmap.
  • Lead stakeholder workshops to align on feasibility, project scope, solution boundaries, delivery dependencies, and client-facing expectations.
  • Define Azure AI/LLM architecture and reference patterns, including agent systems with Foundry Agent Service, Azure OpenAI, and Azure AI Search; enterprise integration through API Management, Logic Apps, and Functions; and governance of identity, private networking, observability, policy controls, and responsible AI gates.
  • Architect model- and tool-agnostic multi-agent systems, including orchestration, tool use, agent memory, context management, MCP/control-plane patterns, and reusable service abstractions.
  • Design the end-to-end data and context layer, including ingestion, preprocessing, synchronization, chunking, embeddings, vector search, knowledge graphs, and semantic retrieval for reliable RAG.
  • Define evaluation frameworks for accuracy, relevance, faithfulness, groundedness, latency, cost, safety, security, and operational reliability.
  • Establish AI security, governance, and observability as centrally enforced design controls, including guardrails, prompt-injection defense, PII protection, access control, audit logging, and OpenTelemetry-style tracing.
  • Maintain architecture decision records, component diagrams, sequence diagrams, design specifications, integration patterns, and reusable reference architecture assets.

Desired Qualifications

  • Azure Solutions Architect Expert, Azure AI Engineer Associate, or Azure Developer certification.
  • Experience with Microsoft Fabric, Semantic Kernel, Prompt Flow, private endpoints, Defender for Cloud, Microsoft 365 Copilot integration, and enterprise Responsible AI controls.
  • Exposure to open-source AI and orchestration frameworks such as LangChain, LangGraph, LlamaIndex, Haystack, Semantic Kernel, MLflow, FastAPI, Docker, and Kubernetes.
  • Experience with responsible AI, model risk management, AI governance boards, red-teaming, human-in-the-loop review, A/B testing, and GenAI FinOps.
  • Experience building reusable enterprise reference architectures, estimation models, accelerators, playbooks, and architecture governance frameworks.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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