Senior Node.js Engineer

We are
We're building the financial infrastructure that powers global innovation. With our cutting-edge suite of embedded payments, cards, and lending solutions, we enable millions of businesses and consumers to transact seamlessly and securely.
The Role
We are looking for a backend engineer who can design, build, and operate highly reliable Node.js services on AWS that enable generative?AI capabilities across our products and internal workflows.
You will create scalable APIs, data pipelines, and serverless architectures that integrate large?language?model (LLM) services such as Amazon Bedrock, OpenAI, and open?source models, enabling teams to safely and efficiently leverage generative AI.
Who You Are
You have experience building Retrieval?Augmented Generation (RAG) systems or knowledge?base chatbots.
You're Hands?on with vector databases such as Pinecone, Chroma, or pgvector on Postgres/Aurora.
Have AWS certification (Developer, Solutions Architect, or Machine Learning Specialty).
Experience with observability tooling (Datadog, New Relic) and cost?optimization strategies for AI workloads.
Background in microservices, domain?driven design, or event?sourcing patterns.
דרישות התפקיד
What You Bring to the Table
?Available working some US hours
Proficient in Hebrew and English both written and verbal, sufficient for achieving consensus and success in a remote and largely asynchronous work environment - Must
4+ years professional experience building production services with Node.js/TypeScript.
3+ years hands?on with AWS, including Lambda, API Gateway, DynamoDB, and at least one container service (ECS, EKS, or Fargate).
Experience integrating third?party or cloud?native LLM services (e.g., Amazon Bedrock, OpenAI API) into production systems.
Strong understanding of RESTful design, GraphQL fundamentals, and event?driven architectures (SNS/SQS, EventBridge).
Proficiency with infrastructure?as?code (AWS CDK, Terraform, or CloudFormation) and CI/CD pipelines.
Familiarity with secure coding, authentication/authorization patterns (Cognito, OAuth), and data privacy best practices for AI workloads.

Technical Environment:
Languages: TypeScript, JavaScript, SQL
Frameworks & Libraries: Express.js, Fastify, Apollo Server, LangChain?JS, AWS SDK v3
Datastores: DynamoDB, Aurora (Postgres + pgvector), Redis, S3
Infra & DevOps: AWS Lambda, API Gateway, ECS/Fargate, Step Functions, CDK, Terraform, Docker, GitHub Actions
AI Stack: Amazon Bedrock, OpenAI API, HuggingFace Inference Endpoints, Pinecone, Chroma