Voya
Financial Services
SeniorAIEngineer,AgenticSystems&RuntimeArchitecture
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“Senior AI Engineer, Agentic Systems & Runtime Architecture at Voya. Skills: Agentic AI systems, Runtime architecture, Multi-agent systems, LLM-powered applications, RAG, AgentOps, Production deployment. Lead the design, build, and operation of production agentic AI systems. Own runtime architecture decisions (orchestration/routing, retrieval strategy, model serving patterns, and runtime controls)”
What You'll Achieve.
Deliver cited, grounded answers via both conversational experiences and programmatic APIs; Measurable, reliable, and safe AI-powered solutions in production; Improve grounding coverage; Manage risk while maintaining iteration speed; Ensure enterprise standards are met; Drive quality, reliability, and risk outcomes; Distinguish “production-grade” from “prototype”; Help shape how agentic systems are governed and operated; Achieve annual performance objectives (for incentive opportunities)
Industry & Context.
Critical Thinking; Thoughtful process of analyzing data and problem solving data to reach a well-reasoned solution
What They're Looking For.
Must Have
Proven experience designing and building LLM-powered applications in production, including prompt/tool orchestration and grounded response patterns., Hands-on experience implementing multi-agent orchestration (planner/supervisor patterns, tool chaining, state management, and conditional routing., understanding of advanced retrieval for RAG: hybrid retrieval, rank fusion concepts, and reranking, with bonus points for contextual retrieval/contextual embeddings approaches., Demonstrated ability to build evaluation systems for non-deterministic AI/agent behavior (rubrics/metrics, regression suites, and release gates), replacing “vibe checks” with systematic improvement loops., Experience with AgentOps / LLMOps practices, including staged rollout models and continuous monitoring for quality, safety, and cost-per-task., security mindset for LLM applications, including awareness of prompt injection (direct and indirect) and defense-in-depth patterns (input sanitization, structured prompts, output validation, least privilege, HITL where appropriate)., Proficiency in Python and modern AI engineering frameworks commonly used for agentic systems (e. g. , graph-based orchestration patterns and RAG integration toolkits)., Experience designing and managing agent memory systems (working, long-term, episodic) and scalable prompt architectures — including version-controlled prompt libraries, hot-swap update patterns, and persona-specific prompt management across multi-agent systems., Experience building production telemetry and diagnosing distributed, multi-hop workflows using tracing/metrics/logs (OpenTelemetry-style concepts are a plus).
Nice to Have
familiarity with Databricks, Azure Foundry and other cloud AI platform patterns and operational requirements for model/agent lifecycle management (versioning, promotion, rollback, policy enforcement, telemetry)., experience in regulated or audit-minded environments where governance, traceability, and operational resilience matter.
What You'll Do.
and operation of production agentic AI systems
Own runtime architecture decisions (orchestration/routing
model serving patterns
and runtime controls)
Evolve capabilities toward more sophisticated agentic design
Collaborate with business and technical stakeholders to translate needs into AI-powered solutions
Architect and build multi-agent workflows
Design and continuously improve retrieval architectures for research assistants
Establish and operationalize AgentOps-style evaluation gates
Implement agentic security controls
Build production-grade observability across multi-step agent executions
Define SLIs/SLOs for reliability and performance
Use telemetry to debug and improve probabilistic runtime behavior
Own reliability outcomes: performance and cost tradeoffs
and incident response
Partner effectively with platform
and governance functions
Ramp up on emerging AI frameworks and tooling
Translate new developments into production-ready implementations with engineering discipline
How You'll Work.
Team & Collaboration
Collaborate with business and technical stakeholders; Partner effectively with platform, security, and governance functions; Work with a team that treats multi-agent systems with the same discipline as distributed systems
Process & Methodology
Staged rollout approaches to manage risk while maintaining iteration speed
Full Job Description
****_Together we fight for everyone’s opportunity for a better financial future._**** We will do this together — with customers, partners and colleagues. We will fight for others, not against: We will stand up for and champion everyone’s access to opportunities. The status quo is not good enough … we believe every individual and every community deserves access to financial opportunities. We are determined to support both individuals and communities in reaching a better financial future. We know that reaching this future depends on our actions today. Like our Purpose Statement, Voya believes in being bold and committed to action. We are committed to a work environment where the differences that we are born with — and those we acquire throughout our lives — are understood, valued and intentionally pursued. We believe that our employees own our culture and have a responsibility to foster an environment where we all feel comfortable bringing our whole selves to work. Purposefully bringing our differences together to positively influence our culture, serve our clients and enrich our communities is essential to our vision. ****Are you ready to join a company with a strong purpose and a winning culture? Start your Voyage – ********Apply Now**** **About the Role** We’re looking for a hands-on Senior AI Engineer to lead the design, build, and operation of production agentic AI systems—including multi-agent research assistants that deliver cited, grounded answers via both conversational experiences and programmatic APIs. You’ll own “runtime architecture” decisions (orchestration/routing, retrieval strategy, model serving patterns, and runtime controls) and help evolve our capabilities toward more sophisticated agentic design: planner/supervisor orchestration, advanced retrieval + reranking, evaluation gates (AgentOps), agentic security, and end-to-end observability. **What You’ll Do** * Collaborate with business and technical stakeholders to translate real-world research and
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