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.
