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What You'll Do

As a Senior GenAI Software Developer, you will:

• Design, develop, test, and deploy AI-powered applications and solutions that address business challenges and improve operational efficiency.
• Partner with business stakeholders, product teams, and technical experts to translate business requirements into scalable technical solutions.
• Build and optimize Generative AI workflows using prompt engineering, AI orchestration frameworks, RAG capabilities, and intelligent automation.
• Design and develop reusable AI skills, prompts, agents, and workflows that can be leveraged across multiple business use cases and teams.
• Develop high-quality, secure, and maintainable code while adhering to enterprise engineering standards and best practices.
• Collaborate on solution architecture, system integrations, APIs, microservices, and cloud-based deployments.
• Lead the delivery of complex Generative AI initiatives from concept through implementation, partnering with technology, business, product, and risk stakeholders to drive successful outcomes and measurable business value.
• Provide technical leadership and guidance to developers and project teams through coaching, knowledge sharing, architecture reviews, and the promotion of engineering best practices.
• Mentor and support team members while helping establish reusable AI patterns, development standards, and governance frameworks that accelerate adoption and delivery across the organization.
• Evaluate emerging AI technologies, frameworks, and tools to identify opportunities for innovation and business value.
• Support continuous improvement through testing, performance optimization, monitoring, debugging, and troubleshooting.
• Participate in the full software development lifecycle, from ideation and design through implementation, deployment, and ongoing maintenance.
• Leverage AI-assisted development tools such as GitHub Copilot and JIRA Rovo to accelerate delivery and improve developer productivity.
• Contribute to responsible AI practices by ensuring solutions align with security, privacy, governance, and risk management requirements.
• Drive innovation by exploring new use cases and applying Generative AI capabilities to transform the way BMO works.

Key Responsibilities

• Translate user needs into technical specifications by understanding, conceptualizing, and facilitating business and technical requirements.
• Analyze, develop, test, and implement software solutions while documenting all phases of the software development lifecycle.
• Perform preventative and corrective maintenance, troubleshooting, and issue resolution for applications and supporting systems.
• Ensure code and configurations adhere to security, logging, error handling, performance, and non-functional requirements.
• Evaluate new technologies and assess their impact on systems, processes, data, and risk.
• Follow release management standards and version control practices.
• Assist in interpreting and documenting client and business requirements.
• Work independently on a range of complex tasks and challenges.
• Exercise sound judgment to identify, diagnose, and resolve issues effectively.
• Take measured risks while protecting the bank by applying BMO's Risk Management Framework and adhering to all applicable policies, standards, laws, and regulatory requirements.
• Broader responsibilities or accountabilities may be assigned as needed.

What Makes You Successful

You are a curious technologist who combines strong software engineering fundamentals with a passion for AI and emerging technologies. You thrive in fast-paced environments, enjoy learning new tools, and are excited by the opportunity to help shape the future of banking through Generative AI while influencing technical direction and mentoring others.

Technical Skills & Experience

• 7+ years of experience in software development, application engineering, AI/ML engineering, or related technical roles, including experience leading complex technology initiatives and mentoring development teams.
• Strong programming and software development experience with modern engineering practices and design patterns.
• Experience leading the design, development, and delivery of enterprise-scale applications, cloud-native solutions, or AI-powered platforms.
• Demonstrated ability to provide technical leadership through architecture reviews, code reviews, engineering standards, and development best practices.
• Experience mentoring junior and intermediate developers and fostering a culture of continuous learning, collaboration, and technical excellence.
• Proven ability to lead cross-functional initiatives involving business, technology, product, architecture, security, and risk stakeholders.
• Experience establishing reusable development patterns, governance frameworks, and scalable engineering practices that drive consistent delivery and adoption.
• Experience developing AI-powered applications using Large Language Models (LLMs) and Generative AI frameworks.
• Design, develop, and deploy intelligent AI agents using AWS AgentCore, enabling scalable automation, business process optimization, and enterprise AI solutions.
• Strong understanding of Retrieval-Augmented Generation (RAG) architectures, vector databases, embeddings, and knowledge retrieval techniques.
• Knowledge of Model Context Protocol (MCP) and integrating AI solutions with enterprise systems, tools, and data sources.
• Experience designing, consuming, and integrating RESTful APIs, including working with Swagger/OpenAPI specifications.
• Experience leveraging GitHub Copilot and other AI-assisted development tools to accelerate software development and improve code quality.
• Ability to design, build, test, and maintain reusable AI skills, prompts, agents, and workflows.
• Strong understanding of LLM model selection, prompt engineering, grounding techniques, token optimization, performance tuning, evaluation methodologies, and cost optimization strategies.
• Skills required: SQL, Prompt Engineering, and JIRA Rovo.
• Experience with cloud computing environments and cloud-native application development.
• Experience with microservices architecture, APIs, and system integrations.
• Knowledge of software testing methodologies, Quality Assurance practices, and Test Driven Development (TDD).
• Understanding of secure software development practices, Responsible AI principles, governance, and enterprise technology standards.
• Experience working within Agile delivery environments and Software Development Lifecycle (SDLC) frameworks.
• Strong troubleshooting and root-cause analysis capabilities.

Foundational Competencies

• Creative Thinking
• Building and Managing Relationships
• Emotional Agility
• Quality Assurance and Testing
• Cloud Computing
• Microservices
• Technology Business Requirements Definition, Analysis and Mapping
• Adaptability
• Learning Agility

Professional Skills

• Strong analytical and problem-solving capabilities.
• Excellent verbal and written communication skills.
• Ability to translate complex technical concepts into business-friendly language.
• Strong collaboration and teamwork skills.
• Proven ability to influence technical decisions and stakeholder outcomes across multiple teams.
• Data-driven decision-making mindset.
• Curiosity and passion for continuous learning and innovation.
• Ability to work independently while contributing to highly collaborative teams.
• Strong coaching and mentoring capabilities.

Nice-to-Have Qualifications

• Experience with Azure OpenAI, Azure AI Foundry, Azure AI Search, Microsoft Copilot Studio, or similar AI platforms.
• Java development experience.
• Experience developing AI agents, multi-agent systems, or conversational AI solutions.
• Familiarity with vector databases and semantic search technologies.
• Knowledge of Responsible AI, AI governance, model evaluation, and AI observability practices.
• Experience building and deploying enterprise-scale GenAI solutions within regulated industries such as banking or financial services.

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