Role Overview

At Voya Investment Management, we are committed to building innovative, responsible, and scalable technology solutions that enable better investment outcomes for our clients. Our vision for AI is grounded in delivering secure, governed, and high-impact capabilities that augment investment decision-making, improve operational efficiency, and enhance client engagement.

Get to Know the Opportunity

As a Director, AI Engineering & Agentic Platform, you will be responsible for designing, building, and operating the AI engineering capabilities. This role is a builder-operator hybrid, focused on delivering production-grade AI systems - not research prototypes - that can be trusted and scaled across investment research, distribution, and operational functions.

You will lead the development of shared AI platform services, including LLM-powered applications, Retrieval-Augmented Generation (RAG) pipelines, and agentic workflows, enabling multiple data science and engineering teams to deliver use cases faster, with stronger governance and reliability.

This role requires a combination of deep technical expertise in LLMOps and AI system architecture, platform thinking, and strong leadership in enterprise environments, particularly within the context of financial services where security, compliance, and trust are critical.

The Contributions You'll Make

AI Platform Architecture & Engineering

• Design and implement scalable AI architectures, including:
  
  • LLM-powered applications
  • Retrieval-Augmented Generation (RAG) systems
  • agentic / multi-step workflows
  • vector search and retrieval services
  • model serving and inference layers
• Establish reusable platform services, APIs, and design patterns to accelerate delivery across multiple teams.
• Define reference architectures and engineering standards for production AI systems.

LLMOps / MLOps Enablement

• Build and operationalize AI delivery pipelines:
  
  • CI/CD for models, prompts, and workflows
  • prompt versioning and lifecycle management
  • evaluation and testing frameworks
  • model and artifact registries
• Implement monitoring for:
  
  • response quality and hallucination control
  • latency, throughput, and system reliability
  • cost observability and optimization
• Establish scalable experimentation and evaluation frameworks to measure AI performance and reliability.

Responsible AI, Governance, and Security

• Design AI systems with strong controls for:
  
  • data security and privacy
  • auditability and traceability
  • entitlements and access controls
  • data lineage and governance
• Partner with risk, compliance, and security teams to embed Responsible AI practices into development and deployment processes.
• Ensure alignment with regulatory expectations and model risk management standards.

Engineering Execution & Operational Excellence

• Lead delivery of production-grade AI systems with a focus on:
  
  • scalability and reliability
  • latency and performance optimization
  • operational readiness and support
• Evaluate and integrate third-party AI platforms and tools where appropriate.
• Drive cost-effective architecture and FinOps practices for AI workloads.

Data Platform Integration

• Partner closely with data engineering and platform teams to integrate AI capabilities with:
  
  • Snowflake and Databricks environments
  • structured and unstructured data pipelines
  • APIs and enterprise data services
  • semantic and knowledge-layer architectures
• Enable seamless access to governed datasets for AI applications.

Leadership & Stakeholder Management

• Serve as a technical leader and advisor to senior stakeholders across business and technology teams.
• Translate business needs into scalable AI platform capabilities and solutions.
• Lead and mentor a team of AI / ML engineers and technical leads.
• Drive adoption of AI capabilities through enablement, best practices, and reusable frameworks.

Minimum Knowledge and Experience

• Bachelor's degree in Computer Science, Engineering, or related field.
• 10+ years of experience in software engineering, ML engineering, or platform engineering.
• 3+ years in a leadership role driving complex engineering initiatives or leading teams.

AI Engineering & Architecture

• Hands-on experience designing and deploying:
  
  • LLM-based applications
  • RAG systems
  • agentic AI workflows
  • vector databases / semantic search solutions
• Strong understanding of prompt engineering patterns and evaluation methodologies.
• Experience with model serving, inference optimization, and production deployment.

ML Engineering / Platform Mindset

• Strong background in building scalable, production-grade systems with focus on:
  
  • reliability and observability
  • latency and performance
  • cost optimization
• Experience developing shared platforms or reusable services across multiple teams.

LLMOps / MLOps

• Experience implementing:
  
  • CI/CD pipelines for ML / AI systems
  • model and artifact registries
  • evaluation and regression pipelines
  • monitoring and alerting frameworks
• Familiarity with prompt lifecycle management and AI system governance controls.

Data Platform & Cloud Technologies

• Strong experience with modern data / AI platforms, including:
  
  • Databricks and/or Snowflake
  • APIs and microservices architectures
  • unstructured data processing pipelines
  • semantic layer or knowledge graph concepts

Enterprise & Financial Services Context

• Experience working in regulated environments with strong requirements for:
  
  • security and data privacy
  • governance and auditability
  • SDLC and change management processes
• Financial services or investment management experience strongly preferred.

Soft Skills

• Excellent communication and stakeholder management skills.
• Ability to influence technical and non-technical audiences.
• Strong problem-solving and strategic thinking capabilities.

Nice to Have

• Experience with Azure AI services, Copilot Studio, or similar enterprise AI tools.
• Familiarity with investment management workflows (research, portfolio construction, risk, distribution).
• Experience building internal AI developer platforms or enablement frameworks.
• Knowledge of FinOps practices for AI and data platforms.
• Exposure to knowledge graphs, semantic layers, or enterprise search platforms.

#LI-LW1

Compensation Pay Disclosure:

Voya is committed to pay that's fair and equitable, which means comparable pay for comparable roles and responsibilities.

The below annual base salary range reflects the expected hiring range(s) for this position in the location(s) listed. In addition to base salary, Voya offers incentive opportunities (i.e., annual cash incentives, sales incentives, and/or long-term incentives) based on the role to reward the achievement of annual performance objectives. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Voya Financial is willing to pay at the time of this posting.

Actual compensation offered may vary from the posted salary range based upon the candidate's geographic location, work experience, education, licensure requirements and/or skill level and will be finalized at the time of offer. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

$180,000-$190,000

Be Well. Stay Well.

Voya provides the resources that can make a difference in your lives. To us, this means thriving physically, financially, socially and emotionally. Voya benefits are designed to help you do just that. That's why we offer an array of plans, programs, tools and resources with one goal in mind: To help you and your family be well and stay well.

What We Offer

• 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

Learn more about Voya benefits (download PDF)

Critical Skills

At Voya, we have identified the following critical skills which are key to success in our culture:

• Customer Focused:
• Critical Thinking:
• Team Mentality:
• Business Acumen:
• Learning Agility:

Learn more aboutCritical Skills