Lead GenAI Backend Platform Software Engineer

The Lead GenAI Backend Platform Software Engineer works independently and develops robust, scalable software solutions across the full stack from cloud infrastructure to backend API integrations to agentic workflows and MCP servers. This role is central to architecting and implementing a cutting‑edge generative AI regulatory chat assistant. The Lead Software Engineer improves overall product quality throughout the software development lifecycle, guides team members in best practices and technical leadership, and helps identify and mitigate architectural risks.

The position reports directly to a Director or Senior Director.

• Design and develop industry-leading solutions that meet defined quality standards, reliability specifications, and strategic objectives
• Lead the architecture of robust, scalable software solutions, with strong focus on backend services (FastAPI, Python) and LLM technologies
• Assist with architecting and developing cloud-native solutions leveraging AWS services, including Bedrock, S3, Fargate, Aurora, Lambda, Step Functions, and emerging technologies
• Collaborate on system architecture decisions and API design, ensuring secure, performant, and maintainable patterns
• Demonstrate solid understanding of systems and processes within the job area and recommend improvements

• Design and implement high-performance, secure APIs using FastAPI and Python, establishing patterns that the team replicates
• Guide the team in industry-leading practices for software development, code quality, system design, and test automation
• Excellent understanding of computer science fundamentals, including algorithm design, problem solving, complexity analysis and data structures
• Lead implementation of comprehensive test strategies, including unit testing, integration testing, and end-to-end testing methodologies; champion test-driven development practices and automated testing frameworks

• Assist with implementing and maintaining CI/CD pipelines, fostering a strong Dev Ops culture within the team
• Help identify gaps between system components and designs and deliver solutions that enable team autonomy
• Take broad perspective to infrastructure problems and exercise independent judgment in selecting techniques and evaluation criteria to obtain results
• Develop actionable insights from analyzing software development trends and software engineering best practices, communicating integration recommendations to management

• Mentor and guide less experienced team members in techniques, processes, and best practices for full-stack development, API design, and system architecture
• Coach and train colleagues in how to write clean, maintainable, secure code and how to think systemically about software design
• Champion collaborative resolution of defects and lead or co‑lead internal process improvement initiatives
• Provide feedback on processes by offering suggestions in line with FINRA's values of collaboration, expertise, innovation, and responsibility

• Work on complex features requiring strong knowledge of generative AI industry practices
• Partner within and across teams to meet shared goals and priorities
• Openly share progress and priorities with key stakeholders, communicating complex or technical information at the right level
• Contribute proactively to the full product development lifecycle, from ideation through deployment

• Develop and refine the system's integration with large language models (LLMs) and generative AI technologies (e.g., agents and MCP servers) as they evolve
• Design secure patterns for handling sensitive data within AI-powered workflows, ensuring compliance with regulatory requirements
• Identify innovative applications of AI/LLM capabilities to improve system functionality and user experience
• Stay informed of advances in LLM frameworks (e.g., Lang Graph, Google ADK, AWS Strands), optimization approaches, and emerging AI capabilities

• Ensure all work products meet or exceed FINRA and team standards for secure development…