Technology Architect

Project Role : Technology Architect Project Role Description : Design and deliver technology architecture for a platform, product, or engagement. Define solutions to meet performance, capability, and scalability needs. Must have skills : Accenture Delivery Architectures (ADA) Good to have skills : NA Minimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Role Summary We are seeking a highly experienced AI Architect with 12+ years of overall experience and deep hands-on expertise across Agentic AI, Generative AI, and Traditional AI/Machine Learning. The role will be responsible for architecting, designing, and governing end-to-end AI solutions—from data and model foundations to agentic workflows and enterprise-scale deployment. The ideal candidate combines strong AI/ML depth, system-level architectural thinking, and practical delivery experience across complex, real-world use cases. Key Responsibilities 1. AI & Agentic Architecture Design end-to-end AI architecture spanning data ingestion, feature engineering, model development, agent orchestration, and application integration Define Agentic AI architectures, including: o Multi-agent collaboration patterns o Tool-using agents and workflow orchestration o Memory, planning, reasoning, and feedback loops Select and apply appropriate agentic design patterns (RAG, Graph-RAG, hierarchical agents, event-driven agents, exception-based agents) 2. Generative AI & LLM Systems Architect Generative AI solutions using LLMs, VLMs, and multimodal models Design and govern: o Prompt engineering and prompt management strategies o RAG pipelines (vector, hybrid, graph-based) o Embedding pipelines and semantic indexing strategies Ensure accuracy, explainability, safety, and cost efficiency of GenAI solutions Define approaches for LLM evaluation, grounding, hallucination mitigation, and guardrails 3. Traditional AI / Machine Learning Provide architectural oversight for classical ML systems, including: o Regression, classification, clustering, anomaly detection, and forecasting o Time-series modeling and predictive analytics Guide model lifecycle management: o Feature engineering strategies o Model selection, validation, and performance metrics o Model drift, data drift, and retraining strategies 4. Data & Platform Architecture Design scalable data architectures supporting AI workloads: o Data lakes / lakehouses o Feature stores o Vector databases o Knowledge graphs Define data quality, data contextualization, and metadata management strategies Collaborate with data engineering teams on ingestion, transformation, and governance pipelines 5. MLOps, LLMOps & AI Governance Architect MLOps / LLMOps frameworks, including: o CI/CD for models and prompts o Model versioning and lineage o Monitoring, observability, and alerting Define AI governance frameworks covering: o Security, privacy, and compliance o Auditability and explainability o Responsible AI and regulatory alignment 6. Enterprise Integration & Delivery Integrate AI systems with enterprise IT and OT systems (ERP, historians, MES, CRM, etc.) Support solution blueprinting, technical design reviews, and architecture sign-offs Act as a technical authority during PoCs, pilots, and scaled deployments Mentor engineers, data scientists, and technical team Required Experience & Skills Experience 12+ years overall experience in software engineering, data, and AI systems 5+ years hands-on experience with ML/AI solutions in production 3+ years of practical experience with Generative AI and/or Agentic AI systems Must Have Strong architectural thinking and abstraction skills Ability to translate business problems into AI solution designs Excellent stakeholder communication and technical storytelling Comfortable working in ambiguous, evolving problem spaces Proven experience influencing technical direction at scale Nice-to-Have Experience with industrial, manufacturing, energy, or enterprise AI use cases Exposure to optimization, simulation, or decision-support systems Contributions to internal AI platforms, accelerators, or reusable frameworks Role Level & Impact Senior / Principal individual contributor or technical leadership role High impact on AI strategy, platform evolution, and solution quality Opportunity to shape next-generation Agentic and Generative AI systems 15 years full time education Important Notice We have been alerted to the existence of fraudulent messages asking job seekers to set up payment to cover various costs associated with establishing employment at Accenture. 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