Director, Engineering - AI & Data Science Platform

TalentAlly · Merrimack, NH · 3 wk ago

Information Technology$126k–$255k/yrFull-time

The Role

Asset Management Technology seeks a Director of Engineering to lead a team focused on AI enablement and Data Science platform capabilities across the product area. This leader will manage engineering delivery for platforms and services that enable teams to experiment with, build, deploy, monitor, and scale AI, GenAI, machine learning, and advanced analytics solutions.

Expertise

Bachelor's degree in Computer Science, Engineering, Data Science, or equivalent experience.
10+ years of software engineering, platform engineering, cloud engineering, data science platform, or AI/ML engineering experience.
5+ years of people leadership experience, including coaching engineers, setting direction, managing delivery, and developing talent.
Experience leading cloud-native platforms and services, preferably in AWS, Kubernetes/EKS, CI/CD, observability, and secure enterprise environments.
Working knowledge of AI/ML lifecycle capabilities, including experimentation, model development, deployment, monitoring, governance, and support.
Experience with GenAI enablement patterns, model gateways, API-based AI services, embeddings, vector stores, LLM integrations, and responsible AI controls.
Strong ability to partner with senior stakeholders, translate business and research needs into platform capabilities, and manage competing priorities across multiple product areas.

The Skills

A strong engineering leader who can build trust, set clear direction, and create a culture of ownership, inclusion, learning, and high-quality execution.
Platform thinking, understanding how to build reusable capabilities, reduce friction for internal customers, and balance reliability, scalability, usability, and cost.
Strong technical judgment across modern software engineering, cloud infrastructure, data science tooling, APIs, automation, security, and operational excellence.
Comfortable leading teams that support both innovation and production-grade platforms, including experimentation environments, developer frameworks, model deployment paths, and operational support models.
Clear communication with engineers, data scientists, product owners, architects, risk partners, and senior leaders.
Commitment to responsible AI, data protection, enterprise controls, and operating within a highly regulated environment.

The Value Delivered

Lead the engineering team responsible for AI and Data Science platform capabilities across Lumin8 and CRISP.
Drive delivery of foundational AI services, developer frameworks, model enablement capabilities, LLM service integrations, embeddings, vector search patterns, and platform support.
Advance CRISP capabilities for data scientists, engineers, and quantitative analysts, including compute, storage, MDEs, workspaces, model development, deployment, monitoring, and collaboration workflows.
Partner with product and architecture leaders to define the roadmap for AI, GenAI, ML, and advanced analytics platform enablement.
Improve developer and data scientist experience through better onboarding, documentation, automation, support, observability, and self-service capabilities.
Ensure platforms are secure, resilient, compliant, cost-aware, and aligned with enterprise technology standards.
Coach and develop engineers, create clear delivery accountability, and foster a team culture focused on innovation, craftsmanship, and measurable business value.

The Team

The AI and Data Science Platforms team enables modern AI, GenAI, machine learning, and analytics workflows across Asset Management Technology. The team supports foundational AI capabilities through Lumin8, including developer frameworks, model enablement, AI service integration, embedding and vector capabilities, gateway patterns, onboarding, and support. The team also supports CRISP, the Computing Research and Innovation System Platform, which provides compute, storage, tooling, collaboration, model development, deployment, monitoring, and experimentation capabilities for data scientists, engineers, and quantitative analysts. The team partners closely with engineering, architecture, data science, security, cloud platform, product, and business stakeholders to deliver reliable, compliant, and easy-to-adopt platform capabilities.