AI Solutions Architect – Enterprise Back-End Systems (Remote)

AI Solutions Architect – Enterprise Back-End Systems (Remote) - ADV TECHMINDS | Career Page

AI Solutions Architect – Enterprise Back-End Systems (Remote)

Bangalore, Karnataka, India

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Job Openings AI Solutions Architect – Enterprise Back-End Systems (Remote)

About the job AI Solutions Architect – Enterprise Back-End Systems (Remote)

Job Title

AI Solutions Architect – Enterprise Back-End Systems

Location

Remote (India)

Work Timings

3:00 PM – 11:00 PM IST

Experience

15+ Years (Minimum 12++ years relevant experience)

Contract Duration

6 Months (Full-Time Consultant)

Role Overview

We are looking for an experienced AI Solutions Architect to lead the design, governance, and implementation of AI-driven capabilities across enterprise back-end systems. The role involves working across CRM, ERP, and iPaaS platforms to deliver intelligent automation and scalable enterprise solutions.

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Key Responsibilities

Design and implement AI-enabled enterprise architecture across CRM, ERP, and integration platforms.

Lead systems integration initiatives ensuring seamless connectivity between enterprise applications.

Develop and deploy AI/ML-based capabilities such as agentic AI systems, LLM-powered workflows, predictive analytics, and intelligent document processing.

Implement and manage integration patterns including REST/GraphQL APIs, event streaming, ETL/ELT pipelines, and webhook-based automation.

Collaborate with engineering teams and executive stakeholders to communicate architecture and technical strategies clearly.

Align architecture and delivery with the Enterprise Technology operating model.

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Required Skills & Experience

10+ years of experience in enterprise solutions architecture, systems integration, or related fields.

Hands-on experience with the following platform categories

CRM

Salesforce, HubSpot, Dynamics 365

ERP

SAP S/4HANA, Oracle, NetSuite

iPaaS

MuleSoft, Boomi, Workato, Azure Integration Services

Experience designing or deploying AI/ML solutions in production environments.

Strong knowledge of API integrations, event-driven architecture, and automation frameworks.

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Preferred Qualifications

Experience with Vector Databases, RAG (Retrieval-Augmented Generation), or AI model fine-tuning.

Knowledge of AI governance frameworks such as NIST AI RMF or EU AI Act.

Familiarity with secure SDLC practices and data privacy standards.

Cloud or enterprise certifications (AWS, Azure, GCP, Salesforce, NetSuite, Workato).

Experience working in regulated industries like Financial Services, Healthcare, or Manufacturing.

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