Job Responsibilities

• Full Stack development of UI Dashboard in React/Typescript and servers in the python stack.
• Deliver data pipelines and ETL on data platforms such as Databricks and Snowflake
• Executes software solutions, design, development, and technical troubleshooting
• This role ensures that large language models (LLMs)—including models such as Claude, ChatGPT, and comparable enterprise-approved models—are used as controlled, well-understood components of the software engineering lifecycle.
• Lead the use of LLMs for structured requirements analysis, including translating business and regulatory requirements into clear technical specifications.
• Establish best practices for prompt-driven design and development, treating prompts as versioned, reviewable engineering artifacts.
• Ensure prompt strategies support determinism, reproducibility, and traceability in regulated environments.
• Ensure LLM-driven systems meet enterprise reliability and resilience expectations.
• The role supervises how LLM-assisted and agent-driven development is performed, ensuring that model strengths, limitations, and risk profiles are understood, documented, and appropriately applied across different classes of software work
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Required Qualifications, Capabilities, and Skills:

• Formal training or certification on software engineering concepts and 5+ years of applied experience
• Strong Python skills and familiarity with agentic development (ADLC)
• Demonstrated Engineering leadership, architecture and stakeholder management skills
• Database design and modeling on modern data platforms (Databricks, snowflake)
• Hands on experience in co-pilot or Claude-code to design and deliver end-to-end applications.
• Working understanding of multi public cloud; exposure to AWS Cloud.
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
• Experience in Risk and Pnl in Markets
• Understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

Preferred qualifications, capabilities, and skills

• Experience in Risk and Pnl in Markets
• Knowledge of Financial Markets and Products (Fixed Income, Derivatives) and Treasury concepts