AI Architect

Ally-eXecutive HR

Gurugram District

On-site

INR 1,500,000 - 2,200,000

Full time

14 days+

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Job summary

A leading HR consultancy is hiring for the position of VP of Technology in Gurugram, India. This role focuses on leading AI/ML innovations for the insurance sector, requiring strong expertise in Microsoft Azure and extensive experience with AI frameworks. Candidates should have a solid understanding of insurance business processes and a history of building scalable AI systems. Competitive package and full-time employment are offered.

Qualifications

7+ years in AI/ML or data science roles.
Experience with Microsoft Azure ecosystem essential.
Ability to lead technical discussions and architectural best practices.

Responsibilities

Design and implement AI/ML solutions.
Lead projects in the insurance domain.
Collaborate with data scientists and ML engineers.

Skills

Microsoft Azure expertise

AI/ML technologies

Large language models

Data science

Software engineering

Education

Bachelor's degree in relevant field

Microsoft Certified: Azure AI Engineer Associate

Google Professional Machine Learning Engineer

Tools

Azure Machine Learning

n8n

TensorFlow

PyTorch

Job description

Direct message the job poster from Ally-eXecutive HR

HIRING NOW - VP of Technology - EMEA + P&C + Lloyd’s mkt exp - 20+ yrs, GGN; APAC region - A/C exe; Sales (retail); P&C Technology Delivery Head -…

Role Summary

Work with us to build modern Insurtech AI underpinned solutions, we are a growing team of hands on architects striving to build high quality solutions for our internal and external customers. The AI Architect is responsible for designing and implementing artificial intelligence and machine learning solutions across the ecosystem. This role combines deep expertise in AI/ML technologies with solution architecture to deliver intelligent, scalable, and responsible AI systems that drive business value.

Microsoft AI Technology Stack - Deep expertise in Azure OpenAI Service (GPT-4, embeddings, document processing), Azure Machine Learning (Automated ML, MLOps, model registry, managed endpoints), Azure AI Services (Document Intelligence, Cognitive Search), Azure AI Studio (prompt flow, evaluation tools), Azure Databricks (unified analytics, MLflow integration), Azure Synapse Analytics, and Microsoft Fabric for integrated data science workloads.

Multi-Platform AI Capabilities - Experience with Google Cloud AI Platform including Vertex AI, Gemini multi-modal capabilities, and BigQuery ML for in-database machine learning on large insurance datasets, balanced with primary Microsoft stack expertise.

AI/ML Frameworks & Model Development - Proficiency in working with large language models (GPT-4, Claude, Gemini, LLaMA) alongside training and fine-tuning small domain-specific models using BERT, DistilBERT, and RoBERTa. Strong command of PyTorch, TensorFlow, scikit-learn, XGBoost, and the Hugging Face ecosystem including Transformers, PEFT for parameter-efficient fine-tuning, and model compression techniques including quantization, pruning, and knowledge distillation.

Orchestration & Automation - Hands‑on experience with n8n workflow orchestration for AI pipeline automation and integration with Azure services, complemented by knowledge of Azure Logic Apps, Power Automate, MLflow for experiment tracking, and Azure DevOps or GitHub Actions for CI/CD pipelines supporting ML operations.

Insurance Domain AI Applications - Practical understanding of AI applications across the insurance value chain including underwriting automation (risk assessment, pricing optimization), claims processing (triage, fraud detection, damage assessment), document processing (OCR, contract analysis, regulatory document understanding), customer service automation, actuarial analytics (loss prediction, reserves estimation), and regulatory compliance automation.

Responsible AI & Governance - Expertise in AI explainability tools (SHAP, LIME, attention visualization), bias detection frameworks (Fairlearn, AI Fairness 360), model risk management, and regulatory compliance frameworks. Deep understanding of AI ethics principles including fairness, accountability, transparency, and privacy-preserving machine learning techniques.

Required Experience

7+ years in software engineering, data science, or AI/ML roles with demonstrable emphasis on the Microsoft Azure ecosystem, including at least 03 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.

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.