Job Overview

Accenture is hiring an AI LLM Technology Architecture Manager in Bengaluru for a senior architecture role focused on enterprise AI, Agentic AI, Generative AI, and intelligent platform engineering. The position is suited to an experienced technology leader who can independently design enterprise-scale AI architectures, guide engineering teams, and translate complex business requirements into secure, scalable, production-ready solutions.

The role is part of Accenture’s Reinvention Deployment Engineering approach, which combines human expertise with AI-driven agents to improve innovation and delivery. The architect will establish reusable architecture patterns, platform standards, governance models, and implementation blueprints for enterprise AI solutions.

Key Responsibilities

• Design end-to-end Agentic AI architectures covering agent topology, memory, context management, orchestration, workflows, and tool integration.
• Define enterprise AI platform architectures using vector databases, semantic search, embeddings, retrieval frameworks, LLM gateways, model routing, and inference optimization.
• Design multi-agent systems with suitable coordination, failover, and tool execution strategies.
• Define integration architectures connecting AI solutions with SAP, Salesforce, ServiceNow, and Appian.
• Develop API, event-driven, streaming, and enterprise integration architecture patterns.
• Establish security and identity approaches for enterprise AI applications.
• Incorporate Responsible AI controls, auditability, traceability, privacy, and regulatory requirements into solution designs.
• Create reusable reference architectures, solution blueprints, platform standards, and technical guidelines.
• Provide hands-on technical direction to engineering and delivery teams.
• Support scalable deployment of AI and GenAI solutions in client environments.
• Guide architecture decisions involving AI modernization, governance, security, scalability, and technology adoption.
• Work with clients and stakeholders to explain architecture choices, risks, and implementation approaches.
• Mentor technical teams and promote engineering quality and continuous improvement.

Required Skills

Candidates should have strong enterprise AI architecture experience and practical knowledge of Agentic AI design. You should understand multi-agent coordination, agent memory, context management, orchestration workflows, tool integration, and reliable failover strategies.

Strong knowledge of enterprise AI platforms is required, including vector databases, semantic search, embeddings, retrieval frameworks, LLM gateways, model routing, inference optimization, and AI cost governance.

The position also requires integration and data architecture expertise. Candidates should understand API architecture and contracts, event-driven systems, streaming platforms, and enterprise integration patterns. Experience with SAP, Salesforce, ServiceNow, and Appian integration is specifically relevant.

Security and Responsible AI are important areas. Candidates should understand OAuth, identity management, Azure AD or enterprise authentication, AI guardrails, bias detection, risk mitigation, audit logging, traceability, privacy, data sovereignty, GDPR, and SOX requirements.

Preferred Skills

Strong solution architecture and technical leadership experience is valuable. Candidates should be comfortable with strategic problem solving, stakeholder and client engagement, technical presentations, team leadership, mentoring, innovation, and technology decision making.

Experience creating enterprise reference architectures, reusable AI patterns, scalable design frameworks, governance standards, modernization strategies, and architecture best practices is particularly useful.

Education

The stated qualification is BE, BTech, or MTech.

Experience

The job information specifies 12 to 16 years of experience. Candidates should have substantial experience in technology architecture, enterprise AI, Agentic AI, Generative AI, or closely related engineering and architecture areas.

Required Technologies

• Artificial Intelligence
• Agentic AI
• Generative AI
• Large Language Models
• Multi-Agent Systems
• Agent Orchestration
• Vector Databases
• Semantic Search
• Embeddings
• Retrieval Frameworks
• LLM Gateway
• Model Routing
• AI Inference Optimization
• SAP
• Salesforce
• ServiceNow
• Appian
• API Architecture
• Event-Driven Architecture
• Kafka
• MSK
• Streaming Platforms
• OAuth
• Azure AD
• Enterprise Authentication
• Responsible AI
• GDPR
• SOX
• Enterprise Integration Patterns

Soft Skills

This senior architecture role requires clear communication and presentation skills because the architect will work with engineering teams, delivery groups, clients, and business stakeholders. Strategic problem solving, technical leadership, mentoring, and cross-functional collaboration are essential for converting complex requirements into practical architecture decisions.

An innovation-focused mindset is also valuable. The role requires balancing emerging AI capabilities with security, governance, scalability, compliance, cost, and business requirements.

Benefits of Working in this Role

The role provides exposure to enterprise-scale AI architecture, Agentic AI platforms, Generative AI, intelligent automation, integration architecture, Responsible AI, and technology modernization. It also offers opportunities to influence architecture standards, guide engineering teams, engage with clients, and create reusable AI solution patterns.

Work Mode

The supplied job description identifies Bengaluru as the location but does not explicitly state an onsite, hybrid, or remote arrangement. Candidates should confirm the applicable work arrangement with Accenture during the recruitment process.

Location

The position is based in Bengaluru, Karnataka, India.

Who Should Apply

This opportunity is best suited to senior technology architects and engineering leaders with extensive enterprise architecture experience and strong exposure to AI, GenAI, LLM, and Agentic AI solutions.

Professionals who have designed multi-agent systems, enterprise AI platforms, integration architectures, security controls, reusable architecture blueprints, or AI modernization strategies should consider applying. Experience with SAP, Salesforce, ServiceNow, Appian, Kafka or MSK, enterprise authentication, and Responsible AI will strengthen alignment with the role.

Career Growth

A senior AI architecture position can strengthen expertise in enterprise AI strategy, Agentic AI, platform architecture, governance, security, integration, and technical leadership. The role also provides scope to influence reusable architecture standards and guide teams delivering AI solutions for enterprise clients.

Application Advice

Tailor your resume to demonstrate architecture ownership rather than listing technologies alone. Highlight enterprise Agentic AI implementations, multi-agent architecture, LLM integration, vector search, embeddings, retrieval solutions, model routing, and AI platform design.

Clearly describe architecture decisions involving SAP, Salesforce, ServiceNow, Appian, APIs, Kafka or MSK, event-driven systems, identity management, security, Responsible AI, compliance, and data privacy. Include examples showing how you created reusable blueprints, improved scalability, guided engineering teams, managed stakeholders, or supported production deployment.

Because this is a senior role, emphasize measurable architecture outcomes, technical leadership, client engagement, mentoring, and strategic technology decisions. Ensure your education and senior-level AI architecture experience are clearly presented.