The company is looking to leverage the full power of Artificial Intelligence, Machine Learning, and Data Science to deliver next-generation AI applications. This role will lead the architecture, engineering, and delivery of enterprise-grade AI solutions within their Corporate Data Office and AI team.
Requirements
- Proven track record architecting and deploying AI solutions at scale using Azure cloud services (Semantic Kernel, Functions, Cosmos DB, Azure AI Search, Azure OpenAI).
- Expert in full-stack development, including front-end (React/Next.js), backend APIs, and cloud-native architectures.
- Strong proficiency in machine learning frameworks (TensorFlow, PyTorch, scikit-learn) and experience with NLP, RAG, and AI agent development.
- Proficiency in AI orchestration frameworks (Semantic Kernel, LangChain) and AI evaluation/observability platforms.
- Experience integrating vector databases and graph databases into AI/ML solutions.
- Hands-on experience with AI workflow orchestration tools like n8n, Airflow, or Prefect.
- Experience implementing AI cost optimization (AI FinOps) and observability practices.
Responsibilities
- Define and own the enterprise AI architecture blueprint to support Retrieval Augmented Generation (RAG), AI agents, machine learning pipelines, and multi-modal AI solutions.
- Architect and implement end-to-end AI applications using Azure Semantic Kernel, Azure Functions, Cosmos DB, Azure AI Search, and modern front-end frameworks (React/Next.js).
- Lead integration of AI solutions with enterprise data sources, APIs, and secure cloud/on-prem environments.
- Design high-availability, secure, and compliant AI systems aligned to enterprise standards.
- Oversee ML model lifecycle management from feature engineering and model training to deployment, monitoring, and retraining.
- Direct data science initiatives that use predictive modeling, NLP, and statistical analysis to inform and optimize business processes.
- Build AI evaluation frameworks with automated testing, benchmarking, and real-time performance monitoring.
Other
- 8+ years of experience in AI/ML engineering, software architecture, or enterprise solution delivery, including at least 3 years in a leadership role.
- Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field; PhD preferred.
- Partner with product, engineering, and business leaders to define AI/ML roadmaps, project priorities, and success metrics.
- Communicate architectural decisions and technical trade-offs to C-level executives and technical teams alike.
- Lead AI engineering and data science standards, governance, and best practices across the organization.
