About the role
Project for a QA and performance platform for customer service and sales teams. Our client helps teams measure and improve agent interactions across email, chat, and voice using structured scorecards. Now they’re building a new layer that automates scoring and generates AI powered explanations.
As a key developer in a cross functional product + ML team, you’ll help architect and build AI’s end-to-end backend infrastructure for scoring and explanation generation at scale.
Our expectations
- 3+ years of AWS backend/serverless experience
- Proficient in Node.js / TypeScript
- Experience writing and deploying Terraform for AWS services
- Familiarity with event driven and batch processing workflows
- Knowledge of LLMs, embeddings, and inference (Claude/GPT/SageMaker)
- Comfort working with PII, security boundaries, and scalable deployments
Nice to have
- Past work with OpenSearch, SageMaker Pipelines, or RDS
- Understanding of Bitbucket Pipelines + AWS CI/CD integrations
- Experience building or integrating RAG pipelines
- Familiarity with Claude via Amazon Bedrock
Main responsibilities
- Develop Lambda functions and ECS Fargate tasks (Node.js + TypeScript)
- Implement and orchestrate Step Functions workflows
- Create secure APIs with API Gateway and Cognito
- Integrate with the Salesforce API
- Write Terraform scripts to provision: Bedrock & SageMaker access, OpenSearch vector stores, Secure VPCs, IAM roles, Cognito pools, RDS databases
- Manage multi environment infrastructure (dev, staging, prod)
- Work with Bitbucket for version control; automate CI/CD via AWS-native tools
- Optimize for cost, performance, security (KMS, redaction, encryption)
