Solution Architect - AI

Accenture in India; Ernakulam; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Accenture in India is seeking an experienced Solution Architect - AI (10+ years) with at least 3 years in AI architecture. The role involves designing scalable, secure AI solutions on AWS, Azure, or GCP, and guiding end-to-end architecture across data, AI/ML, security, and operations for enterprise deployments.

The candidate should master Generative AI, LLMs, RAG, agentic AI and related patterns, and collaborate with business and technology teams to deliver production-ready AI platforms.

Qualifications

• 10+ years of technology experience with 3+ years in AI solution design.
• Experience designing AI/ML/Agentic AI for enterprise, scalable and production-ready.
• Cloud experience on AWS, Azure, or GCP.

Responsibilities

• Design end-to-end AI and Generative AI architectures that meet scalability, security, and reliability.
• Define patterns for Generative AI, Agentic AI, RAG, ML, and intelligent automation.
• Provide architectural leadership across the full solution lifecycle from discovery to production operations.
• Collaborate with stakeholders to evaluate AI use cases and define roadmaps.
• Lead architecture of enterprise AI solutions across cloud and hybrid environments.
• Translate business requirements into scalable and secure architecture designs and diagrams.
• Design AI solutions using AWS, Azure, or GCP services including guardrails and observability.
• Define LLM-based architectures with prompt orchestration, vector search, and knowledge bases.
• Design enterprise integration patterns with APIs, databases, and data platforms.

Skills

Generative AI

Intelligent Automation

Conversational AI

Agentic AI

LLMs

Education

B.Tech/BE/M.Tech/MCA

Tools

Model Context Protocol (MCP)

Agent2Agent (A2A)

Job description

Job Title – Solution Architect - AI – Manager - ACS SONG

Management Level: Level 7 –Manager

Location: Kochi, Coimbatore, Trivandrum, Bangalore

Must have skills: Generative AI, Intelligent Automation, Conversational AI, or Agentic AI, , Large Language Models (LLMs)

Good to have skills: Model Context Protocol (MCP)/ Agent2Agent (A2A)

Experience: 10 - 15 years of experience is required

Educational Qualification: B.Tech/BE/M.Tech/MCA

Job Summary

We are seeking an experienced Solution Architect - AIwith10+ years of overall technology experience, including at least3 years of hands‑off experience designing and architecting AI, Generative AI, Machine Learning, or Agentic AI solutions. The ideal candidate will have a strong background in enterprise solution architecture and experience designing scalable, secure, resilient, and production-ready AI solutions on at least one major cloud platform such asAWS, Microsoft Azure, or Google Cloud Platform (GCP).

The role will be responsible for defining end-to-end AI solution architectures covering application, data, AI/ML, integration, security, infrastructure, and operational components. The architect will work closely with business stakeholders, enterprise architects, data teams, AI engineers, software engineers, security teams, and cloud platform teams to translate business requirements into practical and scalable technology solutions.

The candidate should have strong knowledge of modern AI architecture patterns includingGenerative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, AI agents, vector databases, knowledge retrieval, API/tool integration, model orchestration, observability, security, and responsible AI. Experience in taking AI solutions from initial discovery and proof-of-concept through production deployment and operationalization is essential.

Roles And Responsibilities

• Design end-to-endAI and Generative AI solution architecturesthat address business requirements while meeting enterprise standards for scalability, security, performance, reliability, and maintainability.
• Define appropriate architecture patterns forGenerative AI, Agentic AI, RAG, Machine Learning, intelligent automation, conversational AI, and AI-enabled enterprise applications.
• Provide architectural leadership across the complete solution lifecycle, fromdiscovery, feasibility assessment, architecture definition, prototyping, implementation, production deployment, and post-production operations.
• Collaborate with business and technology stakeholders to evaluate AI use cases, identify suitable technologies, assess technical feasibility, and define implementation roadmaps.
• Lead thearchitecture and solution designof enterprise AI, Generative AI, Machine Learning, and Agentic AI solutions across cloud and hybrid environments.
• Translate business requirements, functional requirements, and non-functional requirements into scalable and securesolution architecture designs, architecture diagrams, integration patterns, and technical specifications.
• Design AI solutions using services & technologies available on AWS, Microsoft Azure, or Google Cloud Platform, including managed AI/ML, data, integration, compute, security, and observability services.
• Define architectures forLLM-based applications, including prompt orchestration, Retrieval-Augmented Generation (RAG), vector search, embeddings, model routing, grounding, knowledge bases, AI agents, tool/function calling, and multi-agent architectures.
• Design enterprise integration patterns connecting AI solutions with APIs, databases, data platforms, SaaS applications, event-driven systems, and external services.
• Evaluate and recommend appropriate foundation models, LLMs, embedding models, AI platforms, vector databases, orchestration frameworks, and supporting technologies based on business, technical, security, cost, and performance requirements.
• Define architecture approaches forAI security, identity and access management, data privacy, guardrails, content filtering, responsible AI, model governance, and regulatory compliance.
• Establish architectural standards forAI observability, monitoring, tracing, logging, evaluation, performance management, reliability, and operational support.
• Work closely with AI engineers, data scientists, data engineers, application developers, DevOps/MLOps teams, cloud engineers, and security teams to guide implementation and ensure alignment with the target architecture.
• Lead architecture reviews, technical design workshops, proof-of-concepts, technology assessments, and design governance activities while communicating complex technical concepts effectively to both technical and business stakeholders.
• Ability to conductAI use-case discovery, technical feasibility assessments, architecture assessments, technology evaluations, and solution option analysis.
• Ability to create and communicatehigh-level architecture, detailed solution architecture, sequence diagrams, data flows, integration diagrams, deployment architectures, and architecture decision records.
• Ability to design appropriateAI guardrailsaddressing areas such as hallucination, prompt injection, data leakage, harmful content, unauthorized tool execution, and inappropriate model responses.
• Ability to definereference architectures, reusable architecture patterns, technical standards, and architecture governance frameworksfor AI solutions.