Director, AI Engineering & Agentic Platform

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.

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.

• 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, including 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 Fin Ops 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.

• 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.

• Hands-on experience designing and deploying LLM-based…