Job Classification:

Technology - Data Analytics & Management

Director, AI Engineer

Job Description

As the Global Asset Management business of Prudential, we’re always looking for ways to improve financial services. We’re passionate about making a meaningful impact - touching the lives of millions and solving financial challenges in an ever-changing world.

We also believe talent is key to achieving our vision and are intentional about building a culture on respect and collaboration. When you join PGIM, you’ll unlock a motivating and impactful career – all while growing your skills and advancing your profession at one of the world’s leading global asset managers!

If you’re not afraid to think differently and challenge the status quo, come and be a part of a dedicated team that’s investing in your future by shaping tomorrow today. At PGIM, You Can!

We are seeking a Director, AI Engineer to lead the design, development, and production deployment of AI-driven systems. This role focuses on advanced machine learning, Generative AI, and Agentic AI applications across investment and enterprise functions. You will be responsible for building the engineering foundation that turns experimental models into scalable, secure, and real-time AI products that support investment research, risk assessment, client intelligence, and decision automation.

This role is based in our office in Newark, NJ. Our organization follows a hybrid work structure where employees can work remotely and/ from the office, as needed, based on demands of specific tasks or personal work preferences. This position is hybrid and requires your on-site presence on a reoccurring weekly basis 3 days per week and can change based on future updates to the company’s in-office presence policy.

Responsibilities

• Lead the end-to-end engineering (Development, Deployment and Promotion to the production systems) of AI/ML systems, ensuring production performance, scalability, and resilience.
• Develop and maintain AI platforms that support LLMs, transformer-based models, and multi-agent orchestration frameworks.
• Translate business and quantitative ideas into fully integrated AI services, APIs, and microservices.
• Engineer agent-based architectures for tasks such as investment intelligence, contextual parsing across different file types, investment research synthesis, and automated reasoning.
• Optimize AI pipelines for real-time inference, multi-tenant usage, and cost-efficiency using cloud-native infrastructure.
• Collaborate across AI research, quantitative, infrastructure, and compliance teams to align design with firm goals and controls.
• Champion engineering best practices in CI/CD, code testing, observability, and model versioning.

Qualifications

• Minimum Master’s degree in Computer Science, Software Engineering, or comparable quantitative disciplines
• 7+ years of experience in software or AI engineering, including experience leading production-grade AI initiatives
• 5+ years of experience working on enterprise cloud platforms (preferably Azure), developing and maintain full-stack applications
• Strong foundation on fundamental cloud services (SaaS, IaaS, PaaS), including automation of deployment using Terraform and cloud templates
• Proficient in building and scaling applications using Python, Java, or Scala
• Strong command of deployment patterns, including containerization (Docker, Kubernetes), cloud orchestration, and inference optimization
• Hands-on experience with Generative AI systems, including LLM fine-tuning, prompt engineering, embedding retrieval, or retrieval-augmented generation (RAG)
• Working knowledge of Agentic AI, LangChain, CrewAI, or custom agent system design
• Understanding of software and data governance, regulatory expectations (e.g., SR 11-7), and observability in financial contexts is preferred
• Strong drive for excellence with minimum level of guidance and supervision
• Excellent communication and leadership skills; able to align engineering priorities with quantitative, investment, and technology stakeholders; Can convince without authority
• Team-orient mindset and can-do attitude

Preferred Qualifications

• Experience in asset management, investment platforms, or financial technology environments
• Familiarity with market data systems, model life-cycle management, and alternative data pipelines
• Exposure to model governance, auditability, and ethical AI standards in regulated sectors

What we offer you:

• Market competitive base salaries, with a yearly bonus potential at every level.