AI/ML Developer

- Design and develop AI-powered agents for software development lifecycle (SDLC) workflows, including code generation, pull request reviews, testing, and engineering automation.

- Build and maintain reusable agentic frameworks, skills libraries, prompts, instructions, and implementation patterns.

- Implement AI-assisted engineering workflows to improve developer productivity, code quality, testing efficiency, and delivery processes.

- Evaluate and integrate GenAI models, agentic frameworks, and AI development tools based on business and engineering requirements.

- Apply spec-driven development practices using tools such as Claude Code and GitHub Copilot to translate requirements and specifications into working solutions.

- Develop and integrate applications using Python, APIs, and enterprise data sources.

- Support automation initiatives across Azure and Databricks Lakehouse environments, identifying opportunities where AI can provide measurable value.

- Work with Databricks and Snowflake to support data integration and AI-enabled workflows.

- Contribute to credit-risk AI extensions and related use cases as business requirements evolve.

- Collaborate directly with client engineering leads to understand requirements, shape solution approaches, and drive implementation independently.

- Validate prototypes for accuracy, reliability, scalability, security, and production readiness.

- Establish reusable development patterns, documentation, and best practices for agentic solutions and AI-assisted engineering.

- Apply sound engineering judgment to determine when AI, agents, conventional automation, or traditional software development is the most appropriate approach.