Solution Architect
Accenture - Bengaluru
Still listed by Accenture · checked today · posted 23 Oct 2026 (yesterday)
Skills: Ai agents, Workflow integration, Retrieval-augmented generation, Uipath processgold, Process mining, LLM, Genai, Agentic ai, Python, SQL, Azure machine learning, Aws sagemaker, Gcp vertex ai, Langchain, Haystack, Mlops, ETL, Data pipelines
**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 : **AI & Data Solution Architecture, UiPath ProcessGold Process Mining, Retrieval-Augmented Generation Minimum 15 year(s) of experience is required **Educational Qualification : **15 years full time education
Summary: As a Solution Architect, a typical day involves leads AI, GenAI, and Agentic automation delivery across 1 to 3 concurrent programs, acting as the shared technical lead. The role sits just above hands-on delivery and below practice ownership — focused on ensuring high-quality AI solutions are designed, governed, and landed well across engagements. The Senior Manager brings together delivery teams, client stakeholders, and architects to drive AI-enabled transformation across Finance, Procurement, Supply Chain, and HR. A key part of the role is translating complex AI concepts into clear, compelling narratives for clients — including preparing and conducting Agentic AI demos.
Roles & Responsibilities:
Agentic AI & Intelligent Automation Solutions Provide technical leadership across 1 to 3 AI delivery programmers, ensuring consistency in design, quality, and approach. Review and guide the design of Agentic AI solutions — multi-agent workflows, LLM integrations, automation pipelines, and orchestration frameworks. Oversee the development of autonomous decision systems such as auto-reconciliation, intelligent document processing, anomaly detection, and forecasting. Ensure AI solutions are embedded effectively into platform architecture and deliver measurable business value — cost reduction, automation, and improved decision accuracy. Guide teams on designing and deploying AI/ML, GenAI, and Agentic models within SaaS platforms — e.g., invoice classification, anomaly detection, demand forecasting, or chatbot automation. Work with Data Architects to ensure data readiness and feature availability across programmes. Align AI delivery with process transformation goals, keeping focus on value realization — accuracy improvement, FTE optimization, and compliance enhancement.
Client Engagement & Demos Prepare and conduct Agentic AI demos for clients — translating technical solutions into clear, business-relevant narratives. Act as a trusted technical advisor for senior client stakeholders, building confidence in AI solutions and delivery approach. Support pre-sales and solution shaping activity — contributing to proposals, workshops, and client discovery sessions. Engage with client IT, transformation sponsors, and analytics teams to align on AI priorities and manage expectations through delivery.
AI Governance, Compliance, and Quality Own AI governance standards across programmes — fairness, transparency, explainability, and data privacy compliance. Ensure all AI deployments comply with Accenture Responsible AI principles and data protection regulations (GDPR, SOC2). Define and track KPIs for model accuracy, drift, and performance manage periodic model reviews across active programmes. Maintain and evolve AI design patterns, delivery templates, and best practices across SaaS deployments. Input into broader enterprise AI governance frameworks where relevant.
Cross-Functional Collaboration Work closely with Enterprise and Functional Architects to ensure AI components align with overall solution blueprints. Partner with Run Support teams to transition models into production with appropriate monitoring in place. Engage Product Managers with feedback on AI feature performance and client adoption insights. Coordinate across delivery teams spanning multiple programmes to share learnings, resolve blockers, and maintain delivery standards.
People & Team Development Lead and mentor AI Managers, data scientists, and analysts across programmes. Support the development of team members through coaching, feedback, and involvement in complex problem solving. Drive enablement for Professional Services teams on AI concepts, prompt design, and agent orchestration workflows.
Continuous Innovation and Enablement Evaluate emerging technologies — LLMs, AutoML, vector databases, retrieval frameworks — for practical SaaS application. Prototype and pilot new AI capabilities that extend platform intelligence, e.g., agent orchestration, autonomous reconciliation, or dynamic forecasting. Contribute reusable assets, delivery accelerators, and whitepapers to the broader practice.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in AI Agents & Workflow Integration, AI & Data Solution Architecture, Retrieval-Augmented Generation, UiPath ProcessGold Process Mining.
- Good To Have Skills: Experience with AI & Data Solution Architecture, Retrieval-Augmented Generation, UiPath ProcessGold Process Mining.
- Strong expertise in integrating artificial intelligence agents within complex workflow environments to optimize business processes. Strong understanding of AI/ML lifecycle management, from model design to deployment. Hands-on experience with GenAI / LLM frameworks (OpenAI, Azure OpenAI, Anthropic, or Google Vertex AI). Proficiency in Python, SQL, and cloud AI tools (Azure Machine Learning, AWS SageMaker, or GCP Vertex AI). Familiarity with ETL/ELT data preparation and data pipeline orchestration in a product/platform-based company. Solid grasp of enterprise process data across Finance, Procurement, or Supply Chain. Understanding of AI/agent orchestration frameworks (LangChain, Haystack, or equivalent). Knowledge of model governance and MLOps principles. Experience preparing and delivering technical AI demos to client and business audiences.
Additional Information:
- The candidate should have minimum 15 years of experience in AI Agents & Workflow Integration.
- 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.
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