AWS Developer

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

1. 3+ years of AWS backend/serverless experience
2. Proficient in Node.js / TypeScript
3. Experience writing and deploying Terraform for AWS services
4. Familiarity with event driven and batch processing workflows
5. Knowledge of LLMs, embeddings, and inference (Claude/GPT/SageMaker)
6. Comfort working with PII, security boundaries, and scalable deployments
7. A good command of English (min. B2 level)

Nice to have

1. Past work with OpenSearch, SageMaker Pipelines, or RDS
2. Understanding of Bitbucket Pipelines + AWS CI/CD integrations
3. Experience building or integrating RAG pipelines
4. Familiarity with Claude via Amazon Bedrock

Main responsibilities

1. Develop Lambda functions and ECS Fargate tasks (Node.js + TypeScript)
2. Implement and orchestrate Step Functions workflows
3. Create secure APIs with API Gateway and Cognito
4. Integrate with the Salesforce API
5. Write Terraform scripts to provision: Bedrock & SageMaker access, OpenSearch vector stores, Secure VPCs, IAM roles, Cognito pools, RDS databases
6. Manage multi environment infrastructure (dev, staging, prod)
7. Work with Bitbucket for version control; automate CI/CD via AWS-native tools
8. Optimize for cost, performance, security (KMS, redaction, encryption)