Lead Technology GenAI Platform

• Strong knowledge of relational databases, including Oracle and MySQL. \n

• Strong knowledge of NoSQL databases, including MongoDB. \n

• Experience processing and integrating large structured and unstructured datasets. \n

\n

Front-End Development

\n \n

• Working knowledge of HTML/CSS, JavaScript, XML, React, and jQuery, with the ability to support end-to-end application delivery. \n, * Experience delivering data analytics, AI, or GenAI solutions. \n

• Familiarity with TensorFlow or PyTorch. \n

• Knowledge of large language model fine-tuning, Retrieval-Augmented Generation (RAG), and tools for agentic AI solutions.

This role combines software engineering, architecture, and technical leadership. You will develop production-ready capabilities, guide engineers, and translate business requirements into reusable, scalable platform solutions. The platform will support a growing portfolio of use cases using proprietary and open-source large language models and large structured and unstructured datasets.

\n

This is an individual contributor role with team leadership responsibilities and substantial hands-on development.

\n

What You’ll Do

\n \n

• Own end-to-end feature delivery, from requirements and architecture through development, testing, deployment, and ongoing improvement. \n

• Design and implement multi-tier, microservices-based application architectures. \n

• Build, optimize, and troubleshoot high-performance APIs using Python and FastAPI. \n

• Implement containerization, distributed caching, and message queues to support scalable, reliable systems. \n

• Integrate business use cases into shared platform capabilities that teams can reuse and extend. \n

• Work with Product Owners and business stakeholders to clarify requirements, prioritize work, and define acceptance criteria. \n

• Break complex initiatives into actionable development tasks, estimates, and delivery plans. \n

• Establish and maintain CI/CD pipelines for automated testing and deployment. \n

• Automate development lifecycle activities to improve delivery speed and reduce manual effort. \n

• Lead code reviews, guide architecture decisions, and apply enterprise engineering standards. \n

• Mentor engineers in solution design, troubleshooting, estimation, and development practices. \n

• Identify performance bottlenecks and implement software enhancements and infrastructure upgrades. \n

• Manage technical debt while maintaining platform quality and supporting continued growth. \n

\n, * Experience with asynchronous programming, Redis or similar distributed caching technologies, and OpenTelemetry. \n

• Knowledge of authentication and authorization mechanisms. \n

• Experience building enterprise platforms in financial services, capital markets, or similarly complex environments. \n

\n

What Success Looks Like in the First 90-120 Days

\n \n

• Feature delivery: Deliver agreed-upon platform features and business use case integrations through testing, acceptance, and deployment. \n

• Scalability and performance: Establish performance baselines, identify bottlenecks, and implement improvements against agreed API and platform performance targets. \n

• Engineering efficiency: Implement or improve automated testing and deployment pipelines, with measurable reductions in manual steps. \n

• Engineering quality: Meet documented acceptance criteria, apply coding and architecture standards, and maintain a prioritized technical debt backlog. \n

• Team execution: Establish clear work breakdowns, estimates, code review practices, and technical guidance that support predictable delivery.