Senior AI Engineer - Wholesale Credit Risk Analytics

Join a pioneering team at the forefront of financial technology innovation. We are building a cutting-edge, agentic AI platform designed to revolutionize the end-to-end credit risk model development lifecycle. By leveraging the power of Large Language Models (LLMs) and intelligent workflows, we aim to augment our quantitative modelers, dramatically increasing their productivity, enhancing model governance, and accelerating the delivery of critical risk models.

We are seeking a senior, hands-on technology leader to drive this transformation. In this role, you will partner directly with quantitative analysts and key stakeholders to shape the most impactful use cases and then lead a team of talented developers to design, build, and deploy the generative AI platform that brings this vision to life.

Key Responsibilities

• Strategic Vision & Stakeholder Partnership:Collaborate closely with quantitative model developers, Model Risk Management (MRM), and business leaders to deeply understand their pain points and translate them into a technical vision and product roadmap.Identify, scope, and prioritize use cases for the agentic workflow platform, ensuring they deliver measurable value and align with strategic objectives.Serve as the primary technical liaison between the engineering team and its users, ensuring a tight feedback loop and continuous alignment.
• Platform Design & Hands-On Development:Lead the architectural design of a scalable, robust, and secure agentic AI platform, including core components for orchestration, knowledge retrieval (e.g. RAG), and tool integration.Engage in hands-on software development to build foundational components, create proofs-of-concept, and tackle the most complex technical challenges.Design and implement secure integrations with internal data sources, external APIs, and various LLMs, ensuring compliance with all data governance and security policies.Establish the CI/CD, testing, logging, and monitoring frameworks required for a mission-critical enterprise application.
• Team Leadership & Mentorship:Lead, mentor, and inspire a team of software engineers, fostering a culture of technical excellence, innovation, and collaboration.Guide the team's architectural decisions, enforce best practices for code quality, and oversee the agile development process.Manage project timelines, resource allocation, and delivery of key platform milestones.

Qualifications:

• Extensive Software Engineering Experience: 10+ years of hands-on experience designing, building, and shipping complex, scalable software systems to production.
• Demonstrable experience in AI Agentic solutions such a for ad hoc data analysis, documentations and workflow orchestration
• Team Leadership: Proven experience leading a software development team, including providing technical mentorship, architectural guidance, and project oversight.
• Expertise in Python: Deep proficiency in Python and its ecosystem of libraries for backend development and data processing and modern AI frameworks such as LangChain
• Practical Generative AI Experience: Demonstrable, hands-on experience building applications using Large Language Models (LLMs). This includes a strong understanding of prompt engineering, retrieval-augmented generation (RAG), and agentic patterns.
• Strong Architectural Skills: Solid understanding of system design, microservices architecture, REST APIs, and event-driven systems.
• Excellent Communication: Ability to effectively communicate complex technical concepts to both technical and non-technical stakeholders and to translate business needs into concrete technical requirements.

Nice-to-Have:

• Financial Domain Knowledge: Experience in the financial services industry, particularly in a quantitative finance, risk management, or Model Risk Management (MRM) context.
• Familiarity with Model Development: Understanding of the market and/or credit risk model development lifecycle (e.g., for PD, LGD, EAD models) and associated regulatory requirements (e.g., SR 11-7, CCAR, CECL, etc.).
• Regulated Environments: Experience building auditable and compliant software within a highly regulated environment.
• Full-Stack Experience: Familiarity with frontend technologies and developing user interfaces for technical workflows.
• Broader Language Proficiency: Experience with Java/C++ in addition to Python.

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