#ACN I&P - GN - SONG - AI & Data - Marketing - MMM NBA - Manager

Accenture in India; Bengaluru; On-site; INR 300,000 - 600,000; Full time

Job summary

Accenture in India seeks an AI Architecture Manager to lead enterprise AI architecture design and governance across large-scale transformations. You will oversee LLM orchestration, agentic AI frameworks, and API integration while guiding a team of AI and data engineers.

Senior client stakeholders will shape AI strategy and roadmaps, with platform-agnostic designs across cloud and hybrid environments. You will establish scalable governance, reusable patterns, and MLOps pipelines for deployment,

Qualifications

• Deep expertise in enterprise AI architecture and governance for large-scale transformation.
• Experience designing end-to-end AI system architectures across cloud/hybrid environments.
• Hands-on MLOps practices including CI/CD for ML, model registries, monitoring, and drift detection.
• Strong API design and integration skills for AI services.

Responsibilities

• Define and own enterprise AI architecture blueprints including LLM integration and multi-agent coordination.
• Design reusable reference architectures and governance patterns for scalable AI deployment.
• Lead LLM orchestration layers, including prompt management and context handling.
• Establish MLOps frameworks for training, deployment, monitoring, and retraining.
• Define API design standards and ensure interoperability across systems.
• Embed responsible AI principles and risk management into architecture decisions.
• Mentor AI/data engineers and drive architectural rigor and innovation.
• Engage with C-level stakeholders to shape AI strategy and roadmaps.
• Evaluate tooling and platforms balancing build vs. buy for long-term scalability.
• Collaborate with data, security, and infra teams to ensure production-ready cost efficiency.

Skills

Enterprise AI Architecture

LLM Orchestration

Agentic AI Frameworks

MLOps

API Design & Integration

AI Governance & Responsible AI

Solution Architecture for AI Transform

LangChain / LlamaIndex

RAG Architecture

Vector Databases

Team Management

Tools

Kubernetes

Docker

Feature Stores

Model Registry & Experiment Tracking (MLflow / W&B)

Event-driven Architecture (Kafka / Pub/Sub)

TOGAF / ArchiMate

Job description

Job Title - AI Architecture Manager | S&C GN
Management Level: 07 - Manager
Location: PAN India
Must Have Skills: Enterprise AI Architecture, LLM Orchestration, Agentic AI Frameworks, MLOps, API Design & Integration, AI Governance & Responsible AI, Solution Architecture for AI Transformation, LangChain / LlamaIndex, RAG Architecture, Vector Databases, Team Management
Good to Have Skills: Kubernetes / Docker, Feature Stores, Model Registry & Experiment Tracking (MLflow / W&B), Event-driven Architecture (Kafka / Pub/Sub), TOGAF / ArchiMate

Job Summary

As an AI Architecture Manager, you will be responsible for designing and governing the architectural blueprints that enable large-scale AI transformation across enterprise environments. Your typical day will involve defining how AI components — including LLMs, agents, ML models, and data pipelines — are structured, coordinated, and deployed across the enterprise. You will lead a team of AI and data engineers, engage with senior client stakeholders to shape AI strategy and platform roadmaps, and establish the reusable patterns, standards, and governance frameworks that ensure AI systems are scalable, reliable, secure, and responsible. You will operate platform-agnostically, designing architectures that work across cloud and hybrid environments.

Roles & Responsibilities

• Define and own enterprise AI architecture blueprints — covering LLM integration, agentic systems, ML pipelines, data flows, and API layers across the enterprise.
• Design reusable AI architecture patterns and reference architectures that standardize how AI components are built, deployed, and governed at scale.
• Lead the architectural design of LLM orchestration layers, including prompt management, context handling, tool use, and multi-agent coordination.
• Establish MLOps frameworks covering model training, versioning, deployment, monitoring, and retraining pipelines across cloud and on-premise environments.
• Define API design standards and integration patterns for AI services, ensuring interoperability across enterprise systems and third-party platforms.
• Embed AI governance, responsible AI principles, and risk management frameworks into architectural design decisions.
• Manage and mentor a team of AI and data engineers, fostering a culture of architectural rigour and technical innovation.
• Engage with C-level and senior client stakeholders to translate enterprise AI transformation objectives into executable architecture roadmaps.
• Evaluate and recommend AI tooling, platforms, and frameworks — balancing build vs. buy decisions with long-term scalability and vendor independence.
• Collaborate with data, security, and infrastructure teams to ensure AI architectures are production-ready, compliant, and cost-efficient.

Professional & Technical Skills

• Must Have Skills: Deep expertise in Enterprise AI Architecture, LLM orchestration, agentic AI frameworks, MLOps, API design & integration, and AI governance; with a proven track record of leading AI architecture initiatives in enterprise transformation programmes.
• Strong ability to design end-to-end AI system architectures — spanning data ingestion, model serving, agent orchestration, and API exposure.
• Deep understanding of LLM orchestration patterns — chaining, tool use, memory, multi-agent systems, and context window management.
• Hands-on experience establishing MLOps practices — CI/CD for ML, model registries, experiment tracking, monitoring, and drift detection.
• Proficiency in API design principles (REST, GraphQL, async patterns) and integration architecture for AI services.
• Experience embedding responsible AI and governance frameworks — bias detection, explainability, audit trails, and compliance controls.
• Ability to design platform-agnostic architectures deployable across major cloud providers (AWS, GCP, Azure) and hybrid environments.
• Strong leadership and communication skills, with experience presenting AI architecture strategies to executive and non-technical audiences.

Additional Information

• The ideal candidate will bring a rare combination of deep AI engineering expertise and enterprise architecture leadership, with a demonstrated ability to design scalable, governed AI systems that accelerate transformation at an enterprise level.
• This position is based at all PAN India offices.

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