Director, AI Engineering & Agentic Platform

Voya Financial • New York, MA

2d • $180,000 - $190,000 • Hybrid

About The Position

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.

Requirements

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

Nice To Haves

• 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.

Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.

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: Director