AI/ML Engineer

Greenlight Financial Technology is the leading family fintech company on a mission to help parents raise financially smart kids. They are seeking an AI/ML Engineer to design, build, and ship production Generative AI applications and ML systems, leading technical design and cross-functional collaboration to enhance AI capabilities across the organization.

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

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
• 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)