Lead Software Engineer – AI Tools

Responsibilities

• Responsible for designing, developing, testing, operating and maintaining Enterprise AI Agents
• Takes full stack ownership by consistently writing production‑ready and testable code
• Consistently creates optimal design adhering to architectural best practices; considers scalability, reliability and performance of systems/contexts affected when defining technical designs
• Performs analysis on failures, proposes design changes, and encourages operational improvements
• Takes feedback from code review and applies changes to meet standards
• Conducts code reviews to provide guidance on engineering best practices and compliance with development procedures
• Accountable for ensuring all aspects of product development follow compliance and security best practices
• Embraces emerging technology opportunities and contributes to the best practices in support of the bank’s technology transformation
• Contributes to a culture of innovation, collaboration and continuous improvement
• Reviews tasks critically and ensures they are appropriately prioritized and sized for incremental delivery; anticipates and communicates blockers and delays before they require escalation

• Bachelor’s degree, or equivalent work experience
• Six to eight years of relevant experience
• 8+ years of development and architectural experience
• Expert in Python Programming with good understanding of other modern programming languages (Java, C#)
• Experience in developing full‑stack applications using React.js, Typescript
• Experience in building applications using Rest API architecture including Auth Flows, Encryption, Observability
• Experience in building and deploying GenAI, Agentic AI Applications using either MCP, Lang Chain, Lang Graph, Semantic Kernel, autogen, Azure AI Foundry
• Developing solutions using RAG architecture patterns and vector databases utilizing Azure AI Services, FAISS etc.
• Good at Git Hub Copilot for accelerated development and understanding on Copilot Studio
• Fundamental understanding of AI/ML models, prompt engineering
• Knowledge on SDLC processes, CI/CD Pipelines, container orchestration

Demonstrates expertise in Python Programming and full‑stack application development, with a strong focus on compliance, security best practices, and architectural design principles. Proficient in building and deploying AI applications using modern technologies and frameworks, while fostering a culture of innovation and continuous improvement.