Manager – Applied Intelligence
GenAI Solutions Architect (Client Solutioning & End-to-End GenAI Apps)
Accenture Applied Intelligence practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition.
As part of our Analytics practice, you will join a worldwide network of smart and driven colleagues experienced in leading tools, methods and applications. From data to analytics and insights to actions, our forward-thinking consultants provide analytically-informed, issue-based insights at scale to help our clients improve outcomes and achieve high performance.
Manager in Applied Intelligence
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GenAI Solutions Architect leads client-facing GenAI solutioning and delivery—translating business problems into secure, scalable GenAI application architectures and roadmaps. They design end-to-end GenAI products (copilots, chatbots, decision assistants, agentic workflows) integrated with enterprise data and systems, and ensure quality through evaluation, guardrails, and responsible AI practices.
Duties and Responsibilities:
- Lead client workshops to understand business objectives, user journeys, and decision workflows; define use case scope, success metrics, and phased roadmap (MVP → scale).
- Own end-to-end solution architecture for GenAI apps:
- Conversation orchestration and tool/function calling patterns
- RAG designs (grounding, retrieval tuning, chunking, reranking, citations)
- Integration with enterprise systems via APIs and workflows
- Non-functional requirements: security, privacy, performance, resiliency, cost
- Design agentic workflows for enterprise use cases: action execution, exception handling, human-in-the-loop approvals, and audit trails.
- Define prompt engineering approach and response controls (templates, few-shot patterns, fallback strategies) and guide implementation.
- Establish evaluation strategy: offline/online testing, golden datasets, regression testing for prompts/retrieval, and continuous improvement loops.
- Drive engineering delivery: backlog, sprint planning, technical governance, integration testing, and production readiness.
- Collaborate with data engineering, BI/analytics, and platform teams to align semantic/knowledge sources and ensure trusted grounding.
- Create client-ready deliverables: architecture diagrams, implementation plan, operating model recommendations, and enablement/training plan.
- Support pursuits and proposals: solution narratives, estimations, staffing plans, and risk/dependency management.
Educational Background/qualifications
- B Tech/M Tech from reputed engineering colleges
- Masters/M Tech in Computer Science
Master degree in Statistics/Econometrics/ Economics from reputed institute
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Requirements:
- 10–12+ years of experience in solution architecture and enterprise application delivery, with strong client-facing ownership.
- Proven experience delivering GenAI solutions (chatbots/copilots/agents) with enterprise integration and production deployment exposure.
- Strong foundation in microservices and cloud-native architecture, API design, and integration patterns.
- Hands-on experience with cloud and container ecosystem (AWS/Azure/GCP, Docker/Kubernetes).
- Strong programming foundation in Python/Java; exposure to React/FastAPI and modern app stacks is a plus.
- Familiarity with MLOps/LLMOps practices and tools (MLflow, Airflow, Kubeflow, Seldon, AzureML, SageMaker) preferred.
- Exposure to data platforms (Databricks/Delta Lake/ADLS, SQL/NoSQL) and enterprise search/vector retrieval preferred.
- Strong stakeholder management, structured problem-solving, and ability to communicate GenAI trade-offs to business and IT leaders.
Soft Skills
- Strategic thinker with a delivery mindset and strong bias for measurable outcomes.
- Excellent communicator and workshop facilitator; comfortable with senior stakeholders.
- Collaborative leader who mentors teams and drives engineering discipline.
Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law.
