AI / ML Developer

Accenture PLC; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Accenture PLC is seeking a visionary AI Architect to design and lead architecture for cutting-edge AI systems, including agent orchestration, LLM integration, and enterprise-scale deployment. You will select models, frameworks, and strategies to enable intelligent multi-agent ecosystems integrated into enterprise environments.

You will drive end-to-end scalability, security, and cost-optimised designs, coordinating with cross-functional teams to ensure production readiness and robust knowledge

Qualifications

• Strong understanding of architecture patterns including knowledge management (RAG, hybrid search), agent design, and enterprise AI.
• Hands-on expertise with LLM orchestration frameworks such as LangGraph, CrewAI, AutoGen, Vertex AI, and AI Refinery.
• Proficiency in tools-as-agents, function calling, API integration, model context protocols (e.g., MCP), and A2A communication.
• Experience with Gen AI safety design, including threat modelling and prompt protection strategies.
• Knowledge of API gateway design, performance optimisation, cost-aware system architecture, and context budgeting.
• Experience in working across cloud-native and hybrid environments with secure enterprise integration patterns.

Responsibilities

• Design the overall AI system architecture, focusing on agent orchestration, system integration, and end-to-end scalability.
• Evaluate and select appropriate LLMs, orchestration frameworks, tools, and APIs aligned with use case complexity and enterprise constraints.
• Architect knowledge management systems using RAG (Retrieval-Augmented Generation) and hybrid search patterns.
• Enable plan-and-execute strategies and multi-agent coordination for complex task automation.
• Ensure secure, cost-optimised design through API gateway integration, token and context-window budgeting, and resource utilisation planning.
• Drive Gen AI threat modelling, safety tier design, and defences against adversarial prompts.
• Collaborate with cross-functional teams to ensure seamless A2A (agent-to-agent) and tool-based orchestration.
• Lead proofs-of-concept, technical assessments, and production readiness for agent-based applications.

Skills

Architecture patterns

Knowledge management

Agent design

Enterprise AI

Gen AI safety

API integration

A2A communication

Threat modelling

LLM orchestration

Education

15-year education

Tools

LangGraph

CrewAI

AutoGen

Vertex AI

AI Refinery

Job description

We are seeking a highly skilled and visionary AI Architect to design and lead the architecture of cutting-edge AI systems involving agent orchestration, LLM integration, and enterprise-scale deployment. You will play a pivotal role in selecting the right models, frameworks, and strategies to enable intelligent multi-agent ecosystems, integrating them seamlessly into existing enterprise environments.

Responsibilities:

• Design the overall AI system architecture, focusing on agent orchestration, system integration, and end-to-end scalability.
• Evaluate and select appropriate LLMs, orchestration frameworks, tools, and APIs aligned with use case complexity and enterprise constraints.
• Architect knowledge management systems using RAG (Retrieval-Augmented Generation) and hybrid search patterns.
• Enable plan-and-execute strategies and multi-agent coordination for complex task automation.
• Ensure secure, cost-optimised design through API gateway integration, token and context-window budgeting, and resource utilisation planning.
• Drive Gen AI threat modelling, safety tier design, and defences against adversarial prompts.
• Collaborate with cross-functional teams to ensure seamless A2A (agent-to-agent) and tool-based orchestration.
• Lead proofs-of-concept, technical assessments, and production readiness for agent-based applications.

Requirements:

• Strong understanding of architecture patterns including knowledge management (RAG, hybrid search), agent design, and enterprise AI.
• Hands-on expertise with LLM orchestration frameworks such as LangGraph, CrewAI, AutoGen, Vertex AI, and AI Refinery.
• Proficiency in tools-as-agents, function calling, API integration, model context protocols (e. g., MCP), and A2A communication.
• Experience with Gen AI safety design, including threat modelling and prompt protection strategies.
• Knowledge of API gateway design, performance optimisation, cost-aware system architecture, and context budgeting.
• Experience in working across cloud-native and hybrid environments with secure enterprise integration patterns.

Additional Information:

• The candidate should have a minimum of 5 years of experience in Large Language Models.
• A 15-year full-time education is required.