OneMain Financial Jobs

Job Overview

This role designs, builds, and maintains the AI-ready data and application infrastructure that powers internal products and client solutions. As part of a new Innovation Team, it partners closely with Data Services and other cross-functional teams to ensure AI solutions integrate well, scale reliably, and deliver value for team members and clients. This a hybrid role based in Cincinnati, OH.

Job Responsibilities

• Partner with internal stakeholders to translate business needs into AI platform requirements (performance, latency, cost, governance, and security).
• Architect and implement AI-enabling infrastructure, including:
  • RAG pipelines, embedding services, retrieval orchestration, and evaluation loops
  • Vector storage/search (e.g., Postgres + pgvector and/or Pinecone), including indexing, metadata filtering, and performance tuning
  • Context/knowledge graphs and metadata frameworks to improve grounding and reuse
  • MCP servers and client integrations to connect AI applications to data
• Build and maintain ingestion and transformation workflows for AI use cases (document processing, chunking, embedding generation, batch/real-time pipelines).
• Develop the core services and integrations that power AI-enhanced applications and agentic tooling (APIs, events/queues, background jobs, caching, permissions, and system integrations).
• Integrate with third party software, cloud storage, and data platforms (e.g., Azure Blob Storage, Snowflake and other sources as applicable) to support ingestion, retrieval, and AI workflows.
• Collaborate closely with others to build software and agentic workflows on top of the platform (tool calling, orchestration, memory/context, and tool/system connectivity).
• Deploy and operate solutions from prototype to production with reliability practices (monitoring, logging/tracing, alerting, incident readiness, and cost controls).
• Implement secure authentication and authorization mechanisms for data and tool access.
• Help implement AI guardrails and governance controls: access patterns, auditability, safe data exposure, and safety/quality checks including human-in-the-loop workflows.
• Perform architecture reviews and platform assessments to improve resilience, security, performance, and maintainability; document standards; provide technical guidance and enablement across teams.
• Stay current on AI infrastructure patterns, tools, and best practices.
• Other duties as assigned.

Qualifications

Bachelor's or Master's degree in Computer Science, Information Systems, or a related field (or equivalent experience).

5 + years in solutions architecture, platform engineering, data architecture, or similar roles; at least 1-2 years of AI/ML platform experience strongly preferred.

Demonstrated ability to implement and operate production systems (not just design), including troubleshooting and performance tuning.

Strong understanding of AI system architecture: RAG/embeddings/vector search, context/knowledge graphs + metadata, model tradeoffs, and agentic workflow enablement (tools/orchestration/memory).

Experience with relational databases and vector retrieval storage, including Postgres + pgvector (preferred) and/or Pinecone.

Cloud architecture experience including security, networking/IAM, and cost management; familiarity with Azure services a plus.

Familiarity with modern delivery/infrastructure tooling (e.g., Docker, CI/CD, and Infrastructure-as-Code).

Experience with modern data platforms and pipelines, including batch processing (scheduled loads) and streaming (continuous/near real-time) data ingestion into warehouses/lakes.

Exper