Back to results

Technology Architect
Accenture
On-site / hybridData Science / ML 1 day ago
Is it worth applying?
AI checks visa and location, seniority and red flags, not just keywords.
??/100
Sign in to score
AI scoring needs a free account: you get 3 free AI scores after signing in.
About the job
Skills mentioned in this posting (12)
CI/CDAIMachine LearningCloudAnalyticsLLMsGenerative AIMLOpsRAGPrompt EngineeringCRMForecasting
Sign in and add your skills to see which ones you're missing.
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
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.