Technology Architect

Accenture PLC

Khordha

On-site

INR 3,000,000 - 9,000,000

Full time

7 days ago
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Job summary

Accenture is seeking a highly experienced AI Architect to lead end‑to‑end AI architecture across data foundations, agentic workflows, and enterprise deployment. This role demands deep expertise in Agentic AI, Generative AI, and traditional ML with hands‑on delivery experience.

The candidate will architect scalable AI platforms, govern model lifecycles, and guide integration with ERP, CRM, and other enterprise systems. 12+ years in software, data and AI are expected.

Qualifications

  • 12+ years of experience in software engineering, data, and AI systems.
  • 5+ years hands-on experience with ML/AI solutions in production.
  • 3+ years practical experience with Generative AI and/or Agentic AI systems.

Responsibilities

  • Design end-to-end AI architecture spanning data ingestion, feature engineering, model development, agent orchestration, and application integration.
  • Define Agentic AI architectures with multi-agent collaboration patterns, tool-using agents, memory, planning, reasoning and feedback loops.
  • Select and apply agentic design patterns (RAG, Graph-RAG, hierarchical agents, event-driven agents).
  • Architect Generative AI solutions using LLMs, VLMs, and multimodal models; design prompt management and RAG pipelines.

Skills

ADA

Education

15 years full time education

Job description

Job Description

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. 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
    • Select and apply appropriate agentic design patterns (RAG, Graph-RAG, hierarchical agents, event-driven agents, exception-based agents)
  2. 2. 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
  3. 3. 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
  4. 4. 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
  5. 5. 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
  6. 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.

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