You turn possibility into production. As an AI Engineer at BWE, you design, build, and refine the tools that bring artificial intelligence into daily business workflows. From LLM-powered copilots to custom integrations and automation, your work helps scale innovation responsibly and reliably. We count on you to make AI real—usable, efficient, and aligned with how we work. 

Responsibilities: 

• Develop and deploy AI applications and integrations using Azure AI services, LLM APIs, Microsoft Power Platform, and third-party AI tools that enhance business productivity. 

• Fine-tune and customize AI models to improve accuracy, relevance, and performance for specific business use cases across origination, closing, and servicing workflows. 

• Monitor and optimize performance of AI systems, ensuring quality, responsiveness, and cost efficiency in production environments. 

• Collaborate with AI Solutions Architect, Business Partners, and end users to understand workflows and deliver usable, intuitive AI-powered tools. 

• Contribute to AI governance frameworks, documentation, and continuous learning around responsible AI use and best practices. 

• Support citizen developers by creating AI components, templates, and integrations that enable business users to build AI-enhanced solutions. 

• Partner with AIOps Engineer to implement monitoring, alerting, and optimization strategies for AI applications and services. 

• Participate in rapid prototyping and proof-of-concept development to validate AI use cases and technical feasibility. 

• Implement security and compliance controls for AI applications ensuring adherence to financial services regulations and data privacy requirements. 

• Research and experiment with emerging AI technologies and techniques to enhance BWE's AI capabilities and competitive advantage. 

• Maintain and update AI application code, deployment pipelines, and integration frameworks as technologies evolve. 

• Provide technical support and troubleshooting for deployed AI solutions across business functions. 

Minimum Qualifications: 

• 3–5 years of experience in AI/ML engineering, automation, software development, or related technical roles. 

• Proficiency with Python and experience working with APIs, Large Language Models (LLMs), and cloud-based AI services. 

• Strong familiarity with Microsoft ecosystem including Azure AI, Power Automate, Power Apps, and Copilot platforms. 

• Experience with AI model deployment, monitoring, and optimization in production environments. 

• Knowledge of software development best practices including version control, testing, and deployment automation. 

• Understanding of data processing, ETL workflows, and integration with enterprise systems. 

• Bachelor's degree in Computer Science, Engineering, Data Science, or related technical field. 

• Ability to balance experimentation and innovation with structured, scalable deployment practices. 

Preferred Qualifications: 

• Experience with multiple AI platforms beyond Microsoft ecosystem (OpenAI, AWS AI, Google Cloud AI). 

• Knowledge of AI model fine-tuning, training, and optimization techniques for enterprise applications. 

• Familiarity with DevOps practices, containerization (Docker, Kubernetes), and CI/CD pipelines for AI applications. 

• Experience in CRE, financial services, or regulated industries with compliance and security requirements. 

• Understanding of AI governance, model risk management, and responsible AI deployment practices. 

• Knowledge of natural language processing, computer vision, or other specialized AI domains. 

• Experience supporting citizen development initiatives and low-code/no-code platform development.