AVP, Applied AI & Engineering

Voya Financial • New York, NY

2d • Hybrid

About The Position

We are looking for a hands-on Applied AI and Engineering leader to help accelerate the practical adoption of AI across Voya Investment Management. This role will focus on applying AI to real business and technology challenges across Investment Management, including investment research, portfolio analytics, operations, distribution, sales, marketing, and technology delivery. The ideal candidate will be able to identify where AI can create value, partner with business and technology stakeholders, guide engineering teams toward scalable solutions, and help transform successful AI capabilities into reusable assets across the organization. You will help bridge Investment Management AI engineering, Data Science, and broader Investment Management technology teams while working closely with AI engineering leaders responsible for agentic platforms, runtime architecture, observability, AI security, and engineering standards. The successful candidate should be equally comfortable discussing investment workflows with business partners, AI solution design with engineers, and business outcomes with senior leadership. Voya is committed to a flexible workplace model. This role may be remote or hybrid, depending on business needs, candidate location, and alignment with the team’s operating model.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, Finance, Business, or a related discipline.
• 10+ years of experience in technology, data science, AI, analytics, software engineering, or digital transformation.
• 5+ years of leadership experience managing technical teams, cross-functional initiatives, or enterprise-scale technology programs.
• Experience delivering AI, analytics, data science, automation, or software solutions into production environments.
• Strong understanding of Generative AI, Agentic AI, AI engineering, intelligent automation, and modern software delivery practices.
• Practical experience translating business problems into AI-enabled solution designs.
• Ability to guide engineers and data scientists while also engaging effectively with business stakeholders.
• Strong communication skills with the ability to explain AI concepts, business value, and implementation tradeoffs to technical and non-technical audiences.
• Demonstrated ability to drive adoption, influence across teams, and deliver measurable business outcomes.

Nice To Haves

• Experience in Asset Management, Investment Management, Wealth Management, Financial Services, or another regulated business environment.
• Experience supporting investment research, portfolio management, investment operations, distribution, sales, marketing, or client-facing business functions.
• Hands-on familiarity with modern AI platforms and engineering tools such as: Databricks Genie AI Snowflake Cortex Microsoft AI Foundry Microsoft 365 Power Platform Python & SQL GitHub Copilot or similar AI-assisted engineering tools
• Experience with: Agentic AI Multi-agent architectures Retrieval-Augmented Generation Semantic search Prompt engineering AI evaluation and monitoring AI workflow automation API and tool integration Reusable engineering frameworks
• Experience leading or mentoring AI engineers, data scientists, software engineers, or technology teams.
• Experience creating reusable technical capabilities, shared services, engineering accelerators, or common implementation patterns.

Responsibilities

• Scale AI Solutions Across Business Domains: Ensure AI solutions are designed for scalability, consistency, extensibility, and business adoption across domains. Promote successful AI solutions across Investment Management and Distribution and expand them into reusable capabilities for related business use cases. Promote collaboration, knowledge sharing, and common practices between AI engineering, data science, and business technology teams. Reuse common assets such as agents, prompt libraries, RAG patterns, evaluation approaches, semantic search, APIs, and workflow automation.
• Lead Applied AI Across Investment Management: Build stronger connectivity between domain-specific AI teams while preserving the business context each team requires. Partner with leaders across investment research, portfolio management, operations, distribution, sales, marketing, and technology to identify practical AI use cases. Translate ambiguous business challenges into scalable AI-enabled solutions. Help business teams move beyond AI experimentation toward production-ready capabilities that improve how work gets done.
• Promote Engineering Scalability Across IM Technology: Drive the adoption of AI-enabled engineering practices across Investment Management technology teams. Help technology teams use AI to improve software development, data engineering, testing, documentation, support, and operational productivity. Promote reusable engineering patterns, accelerators, templates, and implementation approaches. Identify opportunities to apply capabilities built by one team to other areas across Investment Management. Reduce duplicated effort by turning successful AI implementations into reusable capabilities, shared services, and common engineering practices. Encourage disciplined engineering practices for AI solutions, including versioning, testing, evaluation, monitoring, documentation, and production readiness.
• Provide Hands-On AI Solution Leadership: Stay actively involved in AI solution design, architecture discussions, prototyping, and implementation planning. Guide teams in applying modern AI technologies such as Generative AI, Agentic AI, RAG, semantic search, AI agents, and intelligent automation. Evaluate emerging AI tools, frameworks, and platform capabilities for practical use within Investment Management. Mentor AI engineers, data scientists, and technology teams on scalable AI implementation practices. Help teams balance speed, reliability, cost efficiency, maintainability, and business value.
• Partner with AI Engineering and Platform Leaders: Work closely with AI engineering leaders responsible for agentic platforms, multi-agent frameworks, runtime architecture, AgentOps, observability, AI security, and engineering standards. Ensure AI engineering roadmaps remain aligned with Investment Management business priorities. Help define how AI platforms and reusable capabilities can support multiple teams and use cases. Promote scalable implementation approaches across platforms such as Microsoft AI Foundry, Microsoft 365 Copilot, Copilot Studio, Databricks, Snowflake Cortex, Azure AI Services, and related AI engineering frameworks.
• Build AI Capability and Talent Across IM: Mentor developing AI engineers, data scientists, and technology professionals. Help younger AI team members build stronger understanding of Investment Management business workflows. Promote practical AI education, knowledge sharing, and communities of practice across Investment Management technology. Foster a culture of experimentation, engineering excellence, business partnership, and measurable outcomes. Help build a scalable Applied AI capability that can support growing demand across the organization.
• Communicate AI Value and Adoption: Present AI opportunities, implementation plans, and business outcomes to technology and business leadership. Develop clear business cases that connect AI investments to measurable productivity, efficiency, decision quality, and operational improvements. Track adoption, value realization, reuse, and scalability of AI solutions. Serve as a trusted advisor to business and technology stakeholders on practical AI adoption within Investment Management.

Benefits

• Health, dental, vision and life insurance plans
• 401(k) Savings plan – with generous company matching contributions (up to 6%)
• Voya Retirement Plan – employer paid cash balance retirement plan (4%)
• Tuition reimbursement up to $5,250/year
• Paid time off – including 20 days paid time off, nine paid company holidays and a flexible Diversity Celebration Day.
• Paid volunteer time — 40 hours per calendar year

What This Job Offers

• Job Type: Full-time
• Career Level: Manager