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 Competencies
- 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 audiences
- Comfortable operating at multiple levels: strategy, architecture, and implementation.
