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)

Positive 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:
- Multi-agent collaboration patterns
- Tool-using agents and workflow orchestration
- Memory, planning, reasoning, and feedback loops
2. Select and apply appropriate agentic design patterns (RAG, Graph-RAG, hierarchical agents, event-driven agents, exception-based agents)

- Generative AI & LLM Systems

- Architect Generative AI solutions using LLMs, VLMs, and multimodal models
- Design and govern:
- Prompt engineering and prompt management strategies
- RAG pipelines (vector, hybrid, graph-based)




- 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

- Traditional AI / Machine Learning

- Provide architectural oversight for classical ML systems, including:
- Regression, classification, clustering, anomaly detection, and forecasting
- Time-series modeling and predictive analytics

- Guide model lifecycle management:

- Feature engineering strategies
- Model selection, validation, and performance metrics
- Model drift, data drift, and retraining strategies

- Data & Platform Architecture

- Design scalable data architectures supporting AI workloads:
- Data lakes / lakehouses
- Feature stores
- Vector databases
- Knowledge graphs

- Define data quality, data contextualization, and metadata management strategies
- Collaborate with data engineering teams on ingestion, transformation, and governance pipelines

- MLOps, LLMOps & AI Governance

- Architect MLOps / LLMOps frameworks, including:
- CI/CD for models and prompts
- Model versioning and lineage
- Monitoring, observability, and alerting

- Define AI governance frameworks covering:

- Security, privacy, and compliance




- Auditability and explainability
- Responsible AI and regulatory alignment

- 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

Locations

- Job No. ATCI-4929974-S1860125
- Bhubaneswar
- Required Skill: Accenture Delivery Architectures (ADA)

📌 Technology Architect (India)
🏢 Accenture
📍 India