Custom Application Architect at Accenture

Coimbatore, Tamil Nadu, India

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Cloud Computing, AI/MLIndustries

Requirements

Minimum 5 year(s) of experience
Educational Qualification: 15 years full time education
Strong expertise in Google Cloud services: Vertex AI, BigQuery, Pub/Sub, Dataflow, Dataproc, Cloud Functions, Cloud Run, GKE, and IAM
Experience designing and implementing AI/ML pipelines (training, inference, retraining) using Vertex AI Pipelines and MLOps frameworks
Understanding of agent-based architectures, including autonomous orchestration, reasoning frameworks, and contextual memory systems
Proficiency in Python, TensorFlow, PyTorch, and MLflow, and experience integrating models into production systems
Knowledge of data engineering patterns and ETL orchestration with Dataflow or Apache Beam
Familiarity with IaC tools (Terraform, Deployment Manager) and DevOps/MLOps automation
Experience with API design and integration using Apigee or Cloud Endpoints for serving AI APIs and agent interactions
Strong grasp of networking, IAM, VPC design, and data protection best practices on GCP
Excellent communication and presentation skills, able to translate complex AI architectures into business context
Strong collaboration and stakeholder engagement across engineering, AI research, and product management teams
Strategic thinking with the ability to balance innovation, feasibility, and scalability
Exceptional problem-solving, analytical, and conceptual design abilities
Proven experience mentoring engineers and guiding

Responsibilities

Architect and design scalable AI/ML platforms leveraging GCP services such as Vertex AI, Dataflow, BigQuery, Pub/Sub, Cloud Storage, Cloud Run, and GKE
Define and implement multi-agent system architectures using frameworks such as Agent Developer Kit (ADK), LangChain, or Vertex AI Agents
Design end-to-end pipelines for data ingestion, preprocessing, training, inference, and feedback loops
Implement MLOps frameworks for model versioning, deployment, retraining, and observability
Define reference architectures and reusable templates for AI/ML and agentic workloads
Ensure data security, governance, and compliance across model development and agent interactions
Integrate LLMs, knowledge bases, and reasoning components for adaptive and autonomous decision systems
Collaborate with development and DevOps teams to operationalize AI models using CI/CD and IaC best practices
Provide technical leadership, architecture governance, and design reviews for AI and platform initiatives
Stay updated with emerging GCP AI/ML services, agentic frameworks, and industry innovations to drive continuous improvement
Provide functional and/or technical expertise to plan, analyze, define and support the delivery of future functional and technical capabilities for an application or group of applications
Assist in facilitating impact assessment efforts and in producing and reviewing estimates for client work requests

Skills

Google Cloud Platform

GCP Architecture

Vertex AI

Dataflow

BigQuery

Pub/Sub

Cloud Storage

Cloud Run

GKE

AI/ML

MLOps

LangChain

Agent Developer Kit

multi-agent systems

Accenture

Global professional services for digital transformation

About Accenture

Accenture provides a wide range of professional services, including strategy and consulting, technology, and operations, to help organizations improve their performance. Their services assist clients in navigating digital transformation, enhancing operational efficiency, and achieving sustainable growth. Accenture's offerings include cloud migration, cybersecurity, artificial intelligence, and data analytics, which are tailored to meet the needs of various industries such as financial services, healthcare, and retail. What sets Accenture apart from its competitors is its extensive industry knowledge and ability to deliver comprehensive solutions that address both immediate challenges and long-term goals. The company's aim is to support clients in reducing their environmental impact while driving innovation and growth.

Dublin, IrelandHeadquarters

1989Year Founded

$8.5MTotal Funding

IPOCompany Stage

Consulting, Enterprise Software, CybersecurityIndustries

10,001+Employees

Risks

Rapid AI advancements may outpace Accenture's current capabilities, risking competitive disadvantages.

Integration challenges from multiple acquisitions could affect Accenture's operational efficiency.

The rise of AI-driven startups may disrupt Accenture's market share in customer service solutions.

Differentiation

Accenture's acquisitions enhance its capabilities in digital twin technology for financial services.

The company is expanding its expertise in net-zero infrastructure through strategic acquisitions.

Accenture's focus on software-defined vehicles positions it as a leader in automotive innovation.

Upsides

Accenture's investment in EMTECH supports central bank modernization amid digital currency evolution.

The acquisition of Award Solutions boosts Accenture's presence in the growing 5G and IoT markets.

Accenture's strategic acquisitions align with high-growth markets like digital twins and net-zero projects.

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