Senior Specialist - Data Sciences

Role Description

Lead the design development and deployment of enterprisescale AI Machine Learning and Generative AI solutions

Define AI strategy architecture and technology roadmaps aligned with business objectives

Drive endtoend delivery of AI programs from ideation and PoC to production deployment

Architect scalable AI platforms leveraging cloud technologies distributed computing and MLOps practices

Design and implement advanced GenAI solutions using LLMs RAG frameworks agents and multimodal models

Provide technical leadership for AI solution architecture model selection and platform engineering

Develop reusable AI accelerators frameworks and best practices to improve delivery efficiency

Lead crossfunctional teams of AI Engineers Data Scientists Architects and Product Owners

Build AI solutions using Azure AI Services OpenAI Databricks vector databases and modern AI ecosystems

Govern model lifecycle management including training evaluation deployment monitoring and retraining

Define AI security compliance responsible AI and data governance standards across projects

Collaborate with business stakeholders to identify highvalue AI transformation opportunities

Establish enterprise AI architecture patterns and integration strategies with existing systems

Drive innovation by evaluating emerging AI technologies frameworks and industry trends

Lead solution workshops architecture reviews and technical governance forums

Provide thought leadership in AI adoption digital transformation and intelligent automation initiatives

Develop reference architectures for GenAI agentic AI conversational AI and predictive analytics solutions

Ensure scalability performance reliability and cost optimization of AI platforms and services

Mentor senior engineers and architects while fostering a culture of innovation and continuous learning

Support presales activities including solution design effort estimation proposals and client presentations

Work closely with executive leadership to define AI investment priorities and strategic initiatives

Establish KPIs and success metrics to measure business impact and AI solution effectiveness

Drive adoption of DevOps MLOps CICD and AI observability frameworks across teams

Influence enterprisewide AI standards technology selection and modernization programs

Required Skills Python Machine Learning Deep Learning GenAI LLMs RAG Agentic AI LangChain LangGraph Azure AI OpenAI Databricks Vector Databases MLOps Kubernetes Cloud Architecture Data Engineering AI Governance Solution Architecture Stakeholder Management and Team Leadership