Data Scientist Lead

RxLogix Corporation; Dadri; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

RxLogix Corporation is seeking an experienced technical architect to define AI architecture and lead product design initiatives. The ideal candidate should have a strong background in software development, particularly within healthcare frameworks, ensuring patient safety through innovative AI solutions.

Responsibilities include architecting multi-component pipelines, developing MLOps for AI applications, and mentoring AI engineers. The role requires deep knowledge in data privacy compliance and a proven track record in AI systems deployment.

Qualifications

• 10+ years in software development/architecture, with 5+ years in ML/AI.
• Demonstrated experience deploying enterprise-grade AI systems.
• Hands-on experience in healthcare or life sciences platforms.

Responsibilities

• Define AI architecture and multi-year roadmap aligned with business strategy.
• Architect and deploy multi-component pipelines for AI applications.
• Lead internal thought leadership on explainable AI (XAI).

Skills

Software development

Architecture design

Machine Learning

AI systems

Data privacy compliance

Education

Bachelor’s or Master’s in Computer Science, Data Science

PhD (optional)

Tools

MLOps tools

Vector databases

OpenAI APIs

LangChain

Job description

General Purpose: RxLogix Corporation is a niche multinational software company headquartered in Princeton, NJ, USA. We have multiple offices present across US, Europe, Japan and India. RxLogix’s enterprise software applications are used by world’s Top 10 pharma companies like Merck, Johnson & Johnson, Novartis, etc.

RxLogix is seeking experienced technical architects who will be responsible for the overall product architecture and design. Selected candidates will have an opportunity to architect, design and drive our products meant to ensure patient safety around the world. The ideal candidate should have good understanding of the wider enterprise landscape and strong experience of architecting and designing enterprise grade solutions. The candidate should have extensive experience in software development and architecture, design patterns, databases, Integration, usage of third-party libraries and tools.

Key Responsibilities

• Define AI architecture and multi-year roadmap aligned with business strategy and product goals.
• Architect and deploy multi-component pipelines (MCP) combining structured, unstructured, and real-time data for AI applications.
• Develop and maintain RAG (Retrieval-Augmented Generation) pipelines for building domain-specific, context-aware LLM applications.
• Design MLOps pipelines for continuous model training, versioning, deployment, monitoring, and feedback integration.
• Build and scale AI data infrastructure including feature stores, vector databases, and streaming pipelines.
• Drive integration of AI systems with existing compliance and safety modules (e.g., audit trail).
• Evaluate and implement cloud-native, open-source, and proprietary AI frameworks (e.g., LangChain, LlamaIndex, Hugging Face, OpenAI APIs).
• Ensure secure and ethical AI adoption by adhering to GDPR, HIPAA, and internal governance protocols.
• Partner with Engineering, Product, Security, and Regulatory teams to align AI design with system requirements.
• Mentor a growing team of AI engineers and data scientists.
• Lead internal thought leadership on explainable AI (XAI), AI observability, and Responsible AI (RAI).
• Continuously evaluate emerging technologies for real-world application.

Required Qualifications

• Bachelor’s or Master’s in Computer Science, Data Science, or a related field; PhD is a plus.
• 10+ years in software development/architecture, with 5+ years in ML/AI.
• Demonstrated experience deploying enterprise-grade AI systems across predictive, generative, or regulatory domains.
• Hands-on experience in healthcare or life sciences platforms, especially with:
  • Safety signal detection, adverse event classification, intelligent case routing.
  • Document intelligence (OCR, NLP), form ingestion, and summarization.
  • Workflow-aware AI in regulated environments (21 CFR Part 11, GxP).
• Experience with vector databases (e.g., FAISS, Pinecone), embedding models.
• Familiarity with LangChain, LlamaIndex, OpenAI/Anthropic APIs, and orchestrating LLM pipelines.
• Strong understanding of MLOps tools and concepts (CI/CD for ML, feature engineering at scale, experiment tracking).
• Deep knowledge of data privacy and AI compliance standards (GDPR, HIPAA, AI Act).

Preferred Skills

• Experience working in platform-centric SaaS environments.
• Familiarity with product-led AI development.
• Published work, patents, or open-source contributions in AI/ML is a bonus.