Senior Back-End Engineer
Cross River
CloudDistributed SystemsDockerKubernetesPython
Senior Back-End Engineer, Node.js
Cross River
full-time
Posted on:
Location Type: Hybrid
Location: Jerusalem • 🇮🇱 Israel
Visit company websiteJob Level
Senior
Tech Stack
ApolloAWSCloudDockerDynamoDBGraphQLJavaScriptMicroservicesNode.jsPostgresRayRedisTerraformTypeScript
About the role
- Design, build, and operate highly reliable Node.js/TypeScript services on AWS to enable generative‑AI capabilities across products and internal workflows
- Create scalable REST/GraphQL APIs to serve generative‑AI features such as chat, summarization, and content generation
- Build and maintain AWS‑native architectures using Lambda, API Gateway, ECS/Fargate, DynamoDB, S3, and Step Functions
- Integrate and orchestrate LLM services (Amazon Bedrock, OpenAI, HuggingFace, self‑hosted models) and vector databases (Aurora pgvector, Pinecone, Chroma) to power RAG pipelines
- Create secure, observable, and cost‑efficient infrastructure as code (CDK/Terraform) and automate CI/CD with GitHub Actions or AWS CodePipeline
- Implement monitoring, tracing, and logging (CloudWatch, X‑Ray, OpenTelemetry) to track latency, cost, and output quality of AI endpoints
- Collaborate with ML engineers, product managers, and front‑end teams in agile sprints; participate in design reviews and knowledge‑sharing sessions
- Establish best practices for prompt engineering, model evaluation, and data governance to ensure responsible AI usage
- Participate in on‑call/operational activities to ensure production reliability and cost optimization of AI workloads
Requirements
- Available working some US hours
- Proficient in Hebrew and English both written and verbal
- 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 building Retrieval‑Augmented Generation (RAG) systems or knowledge‑base chatbots
- Hands‑on with vector databases such as Pinecone, Chroma, or pgvector on Postgres/Aurora
- Experience integrating third‑party or cloud‑native LLM services (Amazon Bedrock, OpenAI API, HuggingFace, self‑hosted models)
- Familiarity with observability tooling (Datadog, New Relic) and cost‑optimization strategies for AI workloads
- 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 (GitHub Actions, AWS CodePipeline)
- Familiarity with secure coding, authentication/authorization patterns (Cognito, OAuth), and data privacy best practices for AI workloads
- AWS certification (Developer, Solutions Architect, or Machine Learning Specialty) – desirable
- Background in microservices, domain‑driven design, or event‑sourcing patterns
- Experience with Express.js, Fastify, Apollo Server, LangChain‑JS, AWS SDK v3
- Experience with DynamoDB, Aurora (Postgres + pgvector), Redis, S3
- Experience with Docker, ECS/Fargate, Step Functions, CDK, Terraform
Benefits
- Flexible hybrid model: 3 days a week in the office – A must
- ₪1,000 net monthly wellness benefit – from therapy to Pilates to your kid’s art class
- Full Keren Hishtalmut
- Private health & dental insurance
- Donation matching
- Volunteering days
- Team outings and mentorship programs
- Snacks
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
Node.jsTypeScriptAWSREST APIsGraphQLDynamoDBLambdaECSTerraformCI/CD
Soft skills
collaborationcommunicationagile methodologyknowledge sharingproblem solving
Certifications
AWS DeveloperAWS Solutions ArchitectAWS Machine Learning Specialty