Solution Architect

8108 ASOL-Bangalore SEZ Company; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Accenture Bengaluru invites an experienced AI Agentic Architect to lead design and delivery of enterprise-scale AI, GenAI, and multi-agent systems. You will split time between hands-on coding and architectural governance, shaping scalable AI strategies and building production-grade reference implementations.

The role requires 10+ years IT experience with 3+ years in AI/GenAI, and strong knowledge of LangChain, LangGraph, and orchestration frameworks.

Qualifications

• 15 years of full-time education as required.
• Minimum 15 years of professional IT experience in AI/GenAI Architecture.
• Strong hands-on coding and production-grade agentic AI development.
• Experience bridging business strategy and technical execution.

Responsibilities

• Define enterprise AI architecture and roadmap aligned with business goals.
• Design scalable GenAI and Agentic AI solutions for enterprise.
• Lead design reviews, governance, and implementation across teams.
• Prototype agentic systems, govern tool-calling, and memory management.
• Ensure security, observability, and cost governance in AI pipelines.

Skills

AI Agents

Workflow Integration

LangChain

LangGraph

Multi-Agent Systems

Agent Orchestration

Security & Guardrails

Cloud Platforms

Python

Kubernetes

Education

15 years full time education

Tools

LangChain

LangGraph

CrewAI

AutoGen

Semantic Kernel

Azure OpenAI

Job description

Project Role : Solution Architect Project Role Description : Translate client requirements into differentiated, deliverable solutions using in-depth knowledge of a technology, function, or platform. Collaborate with the Sales Pursuit and Delivery Teams to develop a winnable and deliverable solution that underpins the client value proposition and business case. Must have skills : AI Agents & Workflow Integration Good to have skills : NA Minimum 15 year(s) of experience is required Educational Qualification : 15 years full time education

Role Overview : - We are seeking an experienced AI Agentic Architect to lead the design and implementation of enterprise-scale Artificial Intelligence, Generative AI, and Agentic AI solutions. This is a hands-on, player-coach role: you will split your time between architecting production-grade multi-agent systems and writing, reviewing, and setting the standard for the code and patterns your delivery teams build on. Candidates must be genuinely code-fluent from day one — able to build and debug agentic systems personally, not direct from a distance. The ideal candidate will bridge business strategy and technical execution by defining scalable AI architectures, establishing governance standards, and driving AI adoption across the organization and its clients.

Roles & Responsibilities: Enterprise AI Architecture & Strategy Define enterprise AI architecture and roadmap aligned with business objectives. Design scalable and secure AI, GenAI, and Agentic AI solutions. Design end-to-end AI solutions including RAG, AI Agents, Multi-Agent Systems, Knowledge Bases, and AI Workflows. Architect AI integration with enterprise applications, databases, and cloud platforms. Lead technical design reviews and architecture governance activities. Ensure scalability, reliability, observability, and maintainability of AI solutions. Agentic System Design (Hands-On) Design Agentic AI ecosystems using orchestration frameworks, personally prototyping and hardening reference implementations. Agent core mechanics: architect agent orchestration covering planning, reasoning, memory management, context management, task decomposition, and autonomous decision-making. Multi-agent orchestration: design multi-agent patterns such as multi-tier topologies (router domain specialist utility agents), ReAct / ReWOO, and state-machine-based coordination (e.g., LangGraph). Tool-use & integration contracts: design tool/function-calling architectures and Model Context Protocol (MCP) integration layers, enforcing clean, decoupled contracts between agents, MCP servers, and downstream APIs. Agent interoperability: define agent-to-agent communication and delegation using open interoperability standards (e.g., A2A) so specialist agents built on different frameworks can discover and collaborate across accounts. Architect AI copilots, autonomous agents, and workflow automation solutions. Define LLM selection, evaluation, prompt strategy, and guardrails, including build/buy trade-offs across prompting, fine-tuning, and model adaptation for cost and accuracy. Knowledge, Retrieval & Data Architecture Implement enterprise knowledge management and semantic search capabilities. Define data architecture, vector database strategy, and metadata management. Advanced retrieval: architect retrieval strategies beyond baseline RAG — including Graph RAG, hybrid search, and knowledge-graph-grounded systems (e.g., Neo4j, Neptune, RDF/SPARQL) — for higher factual grounding. Establish data governance, security, privacy, and compliance standards. Evaluation, Observability & Reliability Agentic evaluation: design evaluation pipelines that assess full agent trajectories — tool-choice correctness, argument validity, step count, grounding validation, hallucination detection, cost/latency, and policy compliance — not just final outputs. Observability & tracing: define end-to-end tracing and runtime monitoring of agent decisions, tool calls, and outcomes, with continuous quality, cost, and success-rate metrics (e.g., OpenTelemetry, LangSmith / Langfuse, Datadog). Reliability engineering: ensure resilience of agentic systems in production through deterministic state management, error handling, retries/idempotency, fallback and human-in-the-loop escalation, and budget/timeout controls. Define mechanisms for model evaluation, risk management, explainability, and compliance. Governance, Responsible AI & Cost Establish Responsible AI principles and governance controls. Agent lifecycle governance: define registration, configuration, versioning, deprecation, and runtime governance for agents, applying policy-as-code and identity-as-code across design-time and runtime. Agentic cost governance (FinOps): design token-cost budgeting, blast-radius controls, and approval guardrails before autonomous actions with financial or operational impact. Agent security: design defences specific to autonomous systems — prompt-injection mitigation, least-privilege tool-permission scoping, execution sandboxing, and input/output validation across the agent–tool boundary. Ensure AI solutions meet security, legal, and regulatory requirements. Leadership, Delivery & Reusable IP Act as trusted advisor to clients and business leaders. Lead architecture workshops and technical discussions. Mentor AI engineers, solution architects, and development teams — leading by example on code quality and architectural standards. Reusable solution IP: produce reference architectures, solution blueprints, integration guides, and sizing frameworks consumable by field delivery teams across concurrent client accounts.

Professional & Technical Skills: IT experience in AI/GenAI Architecture and hands-on building and deploying agentic AI systems in production. Strong expertise in Generative AI, LLMs, RAG, AI Agents, and Agentic AI. Agentic frameworks: hands-on experience with orchestration frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or equivalent, and agent design patterns (tool-calling, planning/reasoning, memory). Hands-on experience with Azure AI, Azure OpenAI, Azure AI Foundry, AWS AI/ML, or Google Vertex AI. Strong understanding of Machine Learning, NLP, Vector Search, and Knowledge Retrieval. Experience designing enterprise-scale cloud-native architectures. Expertise in Python, APIs, Microservices, Containers, and Kubernetes. Agent operations & security: familiarity with agent evaluation, observability/tracing, and guardrail tooling (e.g., LangSmith, Langfuse, OpenTelemetry, NeMo Guardrails), and with agent security concerns such as prompt injection and tool-permission scoping. Knowledge of security architecture, identity management, and AI governance. Excellent communication and stakeholder management skills. AI Architecture certifications from Azure, AWS, Google, or equivalent. Knowledge of industry-specific AI use cases (Manufacturing, Aerospace, Automotive, BFSI, etc.).

Additional Information: The candidate should have minimum 10+ years of IT experience, with 3+ years in AI/GenAI Architecture and 2+ years hands-on building and deploying agentic AI systems in production. Experience in designing AI-powered enterprise solutions and digital transformation initiatives. Demonstrated experience building and deploying agentic AI systems in production environments. Ability to work with global and cross-functional teams. Experience supporting proposal development, solution estimation, and client presentations. Strong focus on Responsible AI, security, compliance, and governance. Certification in AI Architecture, Cloud Architecture, or Enterprise Architecture is highly desirable.

This position is based at our Bengaluru office. A 15 years full time education is required. 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. Bring your incredible skills and join our global team of innovators. We come together from different backgrounds across the world and work with the latest technologies to create value and growth for our clients. With us, you’ll continue to learn and grow so you can advance in your career. Your personal dreams and ambitions are just as important to us; that’s why we offer support any way we can—when you thrive, we all thrive.

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