Fullstack AI Platform Engineer

About the role

The Intermediate Fullstack AI Platform Engineer will design, build, and maintain production AI agents and agent‑backed workflows on AWS, working across Python backend services and React/TypeScript front‑ends, integrating with Amazon Bedrock and internal systems, and contributing reusable platform patterns to make future agents easier to develop, test, deploy, observe, and maintain.

About the company

Kindsight develops fundraising technology, offering the market’s largest charitable giving database, purpose‑built CRMs, donor prospect research tools, and generative AI that creates personalized content at scale, helping thousands of education, healthcare and nonprofit organizations worldwide raise funds more effectively.

Requirements

• 3–5 years of experience as a full‑stack, backend, AI application, platform‑adjacent, or infrastructure‑focused software engineer
• 1–3 years of Python backend engineering experience
• Hands‑on experience building or integrating AI, LLM, RAG, or agent‑backed applications used by real users
• Experience with at least one agentic framework or orchestration tool (e.g., Strands, LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI)
• Understanding of agentic patterns: tool calling, structured outputs, planning, multi‑turn workflows, session state, memory, retrieval, and evaluation
• Experience defining or consuming structured outputs using JSON, JSON Schema, Pydantic, OpenAPI, or similar
• Experience integrating applications with REST APIs, internal services, external tools, databases, or enterprise systems
• Practical exposure to RAG concepts: embeddings, vector databases, semantic search, document chunking, metadata filtering, retrieval tuning
• Experience with managed LLM services such as Amazon Bedrock, OpenAI, Anthropic, Azure OpenAI, or Vertex AI
• Proficiency in React and TypeScript for building internal tools and API‑integrated screens
• Familiarity with AWS services (Lambda, API Gateway, SQS, DynamoDB, S3, CloudWatch, IAM, Step Functions, Cognito)
• Basic knowledge of infrastructure‑as‑code, CI/CD pipelines, automated testing, and environment‑based deployments
• Strong debugging skills and ability to trace failures from API call through model invocation to tool execution
• Excellent communication skills for explaining trade‑offs and technical decisions