Principal AI Engineer

About the role

We are seeking a Principal GenAI Architect / Forward Deployed Principal Engineer to lead the design, delivery, and productionization of enterprise-grade Generative AI solutions within a highly regulated banking environment.

Responsibilities

• Own and define enterprise-grade GenAI architectures for banking and financial services use cases, including RAG pipelines, agentic workflows, prompt orchestration, and multi-model routing strategies.
• Drive production readiness for GenAI solutions, ensuring scalability, resiliency, observability, latency optimization, security, and cost efficiency.
• Lead complex architectural decisions across data ingestion, vector databases, model selection, guardrails, API scalability, performance optimization, and secure integration with banking systems.
• Establish reference architectures, reusable patterns, and best practices to accelerate responsible GenAI adoption across lines of business.
• Partner with central AI platform teams to align solution architecture with enterprise AI services, platform capabilities, banking technology standards, and long-term roadmap priorities.
• Act as a Forward Deployed Principal Engineer, partnering directly with business, product, and engineering teams to deliver high-impact GenAI use cases from ideation through production.
• Translate banking and financial services business problems into clear AI system designs, technical requirements, and non-functional requirements with measurable outcomes.
• Support GenAI use cases across areas such as customer service, operations, knowledge management, risk, compliance, fraud, employee productivity, document intelligence, and internal workflow automation.
• Troubleshoot and resolve complex issues across non-production and production environments.
• Partner closely with application teams to ensure AI solutions integrate effectively into existing banking platforms, enterprise workflows, data environments, APIs, and control frameworks.
• Influence platform roadmap by feeding real-world banking use-case requirements back into central AI services and enterprise AI platform teams.
• Ensure all AI solutions align with banking risk, cyber, model governance, data protection, privacy, and regulatory expectations.
• Partner with Cyber, Model Risk Management, Legal, Compliance, Risk, and Data Governance teams to design compliant AI patterns without slowing delivery.
• Embed security, privacy, responsible AI, ethical AI, explainability, human oversight, and auditability into solution design by default.
• Help define practical implementation patterns that balance innovation, speed, governance, regulatory expectations, and enterprise control requirements.
• Ensure GenAI solutions are designed with appropriate guardrails for sensitive financial data, customer information, personally identifiable information, and regulated business processes.
• Serve as a recognized GenAI expert across the enterprise, regularly consulted by engineering, architecture, product, risk, compliance, and leadership teams.
• Mentor senior and staff-level engineers and help raise the technical bar across banking technology teams.
• Contribute to internal communities of practice, architecture reviews, executive-level technical discussions, AI governance forums, and knowledge-sharing sessions.
• Represent enterprise GenAI capabilities in internal innovation forums, banking technology discussions, and responsible AI showcases.

Requirements

• 7+ years of software engineering experience, with significant depth in AI/ML, data-intensive systems, distributed systems, or enterprise-scale platforms.
• 2+ years of hands-on Python programming experience.
• 2+ years of experience designing and delivering production-scale Generative AI systems in an enterprise environment.
• 2+ years of experience with LLMs, prompt engineering, and RAG architecture.
• 2+ years of experience with vector databases, semantic search, and retrieval systems.
• 2+ years of experience with API-driven, cloud-native architectures.
• 2+ years of experience with distributed systems, performance optimization, scalability, and reliability engineering.
• Experience working within banking, financial services, fintech, or another highly regulated enterprise environment.
• Strong understanding of banking technology environments and non-functional requirements, including security, scalability, resiliency, observability, latency, auditability, and cost management.
• Demonstrated Principal-level impact, with influence across multiple teams, platforms, business units, or lines of business.
• Experience operating in highly regulated environments, with financial services or banking experience strongly preferred.
• Hands-on experience with agentic AI frameworks, AI workflow orchestration, and multi-model routing.
• Prior experience in a Forward Deployed Engineer, embedded engineering, or business-facing technical delivery model.
• Experience partnering with risk, cyber, legal, compliance, data governance, or model governance teams to deliver production AI solutions.
• Familiarity with banking controls, customer data protection, model risk management, audit requirements, regulatory expectations, and responsible AI principles.
• Ability to communicate complex technical concepts clearly to senior executives, technical stakeholders, risk partners, compliance teams, and non-technical business leaders.

Qualifications

• The ideal candidate is a hands-on Principal-level engineer and architect who can move seamlessly between strategy, architecture, and execution in a banking environment.
• They are comfortable working directly with business teams to understand real-world financial services problems, while also going deep with engineering teams on system design, performance, security, governance, and production readiness.

Skills

• Strong technical judgment, enterprise banking delivery experience, and the ability to build practical, compliant GenAI solutions that can scale responsibly across a large financial institution.

Benefits

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Pay

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Schedule

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