- Location
- Bengaluru, BDC14A, India
- Type
- Full-time
- Department
- Engineering
- Experience
- 12+ years
- Source
- Workday
Description
Project Role Description : Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data.
Must have skills : Machine Learning (ML)
Good to have skills : NA
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
Own the end-to-end architecture of complex enterprise agentic AI solutions. Ensure systems are scalable, secure, observable, reliable, and integrated with enterprise data and applications.
Proven expertise selecting and governing LangGraph, OpenAI Agents SDK, Google ADK, Microsoft Foundry Agent Service, Vertex AI Agent Builder and Amazon Bedrock Agents, including MCP-based tool integration, identity, observability, evaluation and secure production deployment
Must have architected and delivered production AI or ML systems at enterprise scale. Reference architectures, demos, or vendor-platform configuration alone are insufficient.
Roles & Responsibilities:
- Design multi-agent and tool-using AI architectures for complex business workflows.
- Define orchestration, planning, state, memory, context, tool access, and human-approval patterns.
- Make architecture decisions across models, retrieval, applications, data, APIs, security, and cloud.
- Establish requirements for latency, throughput, resilience, cost, and auditability.
- Guide engineering teams from design through deployment and operations.
- Define evaluation, observability, guardrails, fallback, and incident-management patterns.
- Lead architecture reviews and senior client discussions.
Professional & Technical Skills:
- LLM orchestration, tool calling, workflow engines, RAG, and memory architectures.
- Distributed systems, APIs, event-driven architecture, cloud, and enterprise integration.
- LLMOps, tracing, evaluation, security, identity, access control, and cost optimization.
- Build-versus-buy and model-selection trade-offs.15 years full time education
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us at www.accenture.com
Equal Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.