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AI Architect

AI Architect

r3 Consultant

0 years

0 Lacs

noida uttar pradesh india

Posted:1 week ago| Platform:

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Skills Required

ai technology azure openai service processing learning ml model flow evaluation databricks analytics mlflow integration data vertex database stack training tuning pytorch tensorflow xgboost quantization orchestration workflow pipeline automation logic power automate tracking devops github underwriting risk assessment pricing optimization triage ocr analysis estimation compliance visualization management ethics transparency software engineering collaborative governance evidence leadership collaboration design research experimentation certifications

Work Mode

On-site

Job Type

Full Time

Job Description

Required Skills

Microsoft AI Technology Stack

Multi-Platform AI Capabilities

AI/ML Frameworks & Model Development

Orchestration & Automation

Insurance Domain AI Applications

Responsible AI & Governance

Required Experience

Seven or more years in software engineering, data science, or AI/ML roles with demonstrable emphasis on the Microsoft Azure ecosystem, including at least three years architecting and deploying production AI/ML systems at scale, preferably within insurance or financial services environments. Proven track record of training and fine-tuning small language models for domain-specific business processes, with strong collaborative experience working alongside AI/ML teams, data scientists, and ML engineers.
Hands-on experience implementing n8n workflow orchestration for AI pipelines, establishing AI governance frameworks in regulated industries, and working with both public LLMs and private custom model deployments. Demonstrated success building insurance-specific AI solutions and designing hybrid architectures that combine large and small models for cost-effective, high-performance systems. Evidence of improving existing AI systems and processes through architectural innovation and best practices.

Key Competencies

Insurance Domain Knowledge - Understanding of insurance business processes, data structures, regulatory requirements, actuarial concepts, and risk modeling principles specific to the insurance industry.

Technical Leadership & Collaboration - Demonstrated ability to work effectively with existing AI experts and teams, mentor data scientists and ML engineers on architectural best practices, lead technical discussions and design reviews, and bridge the gap between AI research and production implementation.

Innovation & Continuous Improvement - Commitment to staying current with AI/ML research and industry trends, evaluating emerging technologies for organizational adoption, driving proof-of-concepts for innovative insurance AI applications, and fostering a culture of experimentation and continuous learning.

Certifications

Microsoft Certified: Azure AI Engineer Associate (AI-102), Microsoft Certified: Azure Data Scientist Associate (DP-100), and Microsoft Certified: Azure Solutions Architect Expert (AZ-305). Additional valuable certifications include Google Professional Machine Learning Engineer.

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