Skip to content
ReferMeAJob
LiveFull-timeApply by 1 Nov 2026

AI Architect

Pune, Maharashtra, India

Experience
12–15 years
Employment
Full-time
Work mode
Onsite
Salary
₹24.1 L–28.9 L / year
Deadline
Apply by 1 Nov 2026
Posted
2025-12-17

About the role

AI Architect:

Location : Pune (WFO)-4 Days / Hyderabad(only immediate joiner)

Duration-6 Months

NP-0-15 days.

Product Architect - AI/ML

Location: India/Offshore

Experience: 12-15 years (Minimum 6-7 years in AI/ML Product Architecture)

Location: -Pune (4 Days WFO)

No. of Position:1

Type of Hire: Contract to Contract

Role Overview

Define and drive the technical product vision for enterprise AI/ML platforms in healthcare,

translating business requirements into scalable architectures while ensuring delivery

excellence and long-term product sustainability. This role requires hands-on leadership,

flexible collaboration across time zones, and the ability to mentor engineering teams.

Product & Technical Strategy

• Architect end-to-end product solutions for processing clinical records, claims, and

healthcare documentation

• Design hybrid Azure/on-premises architectures supporting multi-tenant SaaS and

enterprise deployment models

• Establish product architecture principles, design patterns, and technology stack

decisions

• Evaluate build-vs-buy decisions for AI capabilities, Drive technical feasibility

assessments and rapid prototyping for new product features

• Own non-functional requirements: performance, security, compliance (HIPAA),

scalability, reliability

• Present architectural proposals and technical roadmaps to leadership through clear

presentations and documentation AI/ML Product Engineering

• Design and implement fine-tuning pipelines for domain-specific LLMs (e.g. Llama,

Mistral, Phi-3) on medical datasets

• Architect MLOps frameworks enabling continuous model improvement: training,

evaluation, deployment, monitoring

• Build “built-in-intelligence-products” using advanced AI models.

• Implement distributed training infrastructure on Azure ML with GPU optimization

(RTX5090/4090/A100/H100 clusters)

• Create model evaluation frameworks with domain-specific metrics and quality

benchmarks

• Develop synthetic data generation capabilities for model training and testing

• Establish model versioning, A/B testing, and rollback strategies for production

deployments Platform & Infrastructure

• Design microservices architectures with Azure Kubernetes Service, Service Bus, Event

Hubs for event-driven workflows

• Build scalable data pipelines using Azure Data Factory, Synapse Analytics, Databricks for

high-volume processing

• Implement CI/CD automation through Azure DevOps with comprehensive testing and

deployment gates

• Architect observability solutions: monitoring, logging, alerting, performance analytics

• Design hybrid cloud integration patterns connecting Azure services with on-premises

systems

• Manage data architecture: Azure SQL, Cosmos DB, blob storage, data lakes with lifecycle

policies Delivery Excellence & Hands-On Leadership

• Lead proof-of-concept execution from inception to production-ready solutions within

defined timelines

• Conduct rigorous code reviews ensuring adherence to standards, performance

optimization, and maintainability

• Roll up sleeves for critical implementation work: debugging production issues, optimizing

model performance, refactoring complex modules

• Deliver technical demos to internal stakeholders and customers showcasing product

capabilities

• Establish engineering excellence standards: code quality, testing frameworks, peer

reviews, documentation

• Create comprehensive technical documentation: architecture decision records, API

contracts, deployment guides

• Identify and systematically address technical debt across AI models, infrastructure, and

codebase Team Development & Collaboration

• Mentor and develop junior engineers and fresh graduates through pair programming, and

technical guidance

• Review and provide constructive feedback on designs, code, and technical approaches

from team members

• Foster engineering culture emphasizing quality, innovation, and continuous learning

• Collaborate with US-based teams requiring flexibility for meetings during early morning or

late evening IST hours

• Bridge communication between offshore development teams and US-based

product/business stakeholders • Translate business requirements from US teams into

actionable technical tasks for India-based engineers

• Participate in cross-timezone planning, sprint reviews, and architecture discussions

Required Qualifications • [Non Negotiable] Expert Python development with PyTorch,

Transformers, production ML frameworks • [Non Negotiable] Comfortable handling

NVIDIA/CUDA variants and their inner workings.

• [Non Negotiable] Proven experience fine-tuning LLMs and deploying custom models in

regulated environments • [Non Negotiable] Track record of shipping production AI products

with measurable business impact

• [Non Negotiable] Core Software Engineering skills. AI/ ML expertise, DevOps.

• [Non Negotiable] Flexibility to work with US hours overlap Key Competencie

• Hands-on technical leadership and a user-centric approach to technical architecture

• Ownership mindset with accountability for outcomes and the ability to balance

innovation with pragmatic engineering

• Effective communicator capable of engaging both technical and non-technical audience