AI/ML Engineer

Greenlight Financial TechnologyAtlanta, GA
1dHybrid

About The Position

Greenlight is the leading family fintech company on a mission to help parents raise financially smart kids. We proudly serve more than 6 million parents and kids with our award-winning banking app for families. With Greenlight, parents can automate allowance, manage chores, set flexible spend controls, and invest for their family’s future. Kids and teens learn to earn, save, spend wisely, and invest. At Greenlight, we believe every child should have the opportunity to become financially healthy and happy. It’s no small task, and that’s why we leap out of bed every morning to come to work. Because creating a better, brighter future for the next generation depends on it. We are looking for an AI/ML Engineer to join our AI team. The AI/ML Engineer designs, builds, and ships production Generative AI applications, AI agents, and ML systems for customer-facing and internal products. The role pairs deep expertise in large language models and agentic architectures with senior-level software engineering to deliver scalable, secure AI solutions. This engineer leads technical design of complex AI systems, drives cross-functional collaboration with product, platform, and security teams, and shapes the strategic direction of AI/ML capabilities across the organization.

Requirements

  • Extensive experience building and deploying AI agents and Generative AI applications in production.
  • Deep knowledge of LLMs, agentic architectures, multi-agent systems, RAG, vector search, tool use/function calling, prompt engineering, and fine-tuning.
  • Hands-on experience with AI/ML frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent.
  • Strong software engineering skills building production microservices and APIs in Python or JavaScript/TypeScript.
  • Experience designing auth systems for AI applications: OAuth, token-based access control, and delegated authorization.
  • Proficiency with a major cloud ML platform (Databricks, AWS SageMaker, or Google Vertex AI) for deployment and serving.
  • Ability to produce clear technical design documentation and architecture specs for complex systems.
  • Strong cross-functional communication and collaboration across product, engineering, security, and operations.

Nice To Haves

  • Experience with CI/CD pipelines and infrastructure tooling (GitHub Actions, Jenkins, Kubernetes, Terraform).
  • Experience with a JVM language (Java, Kotlin, or Scala) for backend service development.
  • Background in data pipeline and streaming tools (Airflow, Spark).

Responsibilities

  • Design, build, and deploy production AI agents and multi-agent orchestration systems with prompt engineering, LLM chaining, and tool-calling patterns for complex, multi-step workflows.
  • Architect RAG pipelines with vector search, hybrid retrieval, and knowledge base management for AI-driven question-answering and decision-support.
  • Integrate third-party AI platforms and LLM providers, designing authentication flows, tool schemas, and agent-to-backend communication.
  • Design AI agent security architectures including token exchange, delegated access, and user verification flows for systems acting on behalf of users.
  • Build production microservices and APIs (FastAPI, Flask, Node.js) serving as orchestration layers and tool endpoints for AI agent systems.
  • Architect authentication and authorization for AI services: identity provider integration, token validation, and service-to-service auth.
  • Deploy, monitor, and maintain ML models and AI agent endpoints on cloud platforms (Databricks, AWS SageMaker) including scaling and health management.
  • Build data ETL pipelines for feature engineering, transaction processing, and knowledge base ingestion.
  • Develop evaluation and monitoring frameworks for non-deterministic AI systems: agent correctness testing, retrieval quality, and alerting.
  • Author technical design docs, architecture diagrams, and API contracts; mentor junior and mid-level engineers on AI development practices.
  • Lead architecture reviews and produce design documents with implementation roadmaps; evaluate emerging AI technologies to inform team strategy.
  • Collaborate cross-functionally with product, platform, security, and operations to define requirements, prioritize features, and ship AI integrations end-to-end.

Benefits

  • Medical, dental, vision, and HSA match
  • Paid life insurance, AD&D, and disability benefits
  • Traditional 401k with company match
  • Unlimited PTO
  • Paid company holidays and pop-up bonus holidays
  • Professional development stipends
  • Mental health resources
  • 1:1 financial planners
  • Fertility healthcare
  • 100% paid parental and caregiving leave, plus cleaning service and meals during your leave
  • Flexible WFH, both remote and in-office opportunities
  • Fully stocked kitchen, catered lunches, and occasional in-office happy hours
  • Employee resource groups
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