Senior/Lead Backend Engineer with AWS

Job Description

Must Have:

• 7+ years of experience developing with a modern programming language.
• Proven experience designing scalable, event-driven serverless architectures on AWS, specifically utilizing Lambda, API Gateway, DynamoDB, S3, and EventBridge.
• Proficiency with Infrastructure-as-Code frameworks, specifically the AWS Cloud Development Kit (CDK).
• Hands-on experience implementing vector databases and RAG (Retrieval-Augmented Generation) pipelines using technologies like OpenSearch vector engine, Pinecone, Weaviate, FAISS, or Amazon Kendra.
• Deep understanding of embedding generation, similarity search, and context retrieval techniques.
• Experience building secure and repeatable CI/CD pipelines using GitHub Actions.
• Familiarity with implementing distributed tracing and observability using OpenTelemetry in serverless or microservice environments.
• Excellent communication and collaboration skills, with the ability to work closely with cross-functional teams, including AI engineering.

Nice to Have:

• Experience building real-time WebSocket applications.
• Familiarity with AWS AI services, specifically Amazon Bedrock or SageMaker model deployment workflows.
• Exposure to LLM orchestration frameworks such as LangChain or semantic caching strategies.
• Strong understanding of security, cost optimization, and resilience strategies for large-scale serverless applications.

Job Responsibilities

• Design, build, and maintain a scalable event-driven serverless application using the AWS Cloud Development Kit (CDK).
• Architect and implement backend solutions leveraging API Gateway (REST and WebSocket APIs), AWS Lambda with efficient scaling, Amazon S3 for object storage, Amazon DynamoDB for persistence, and EventBridge for orchestration.
• Manage the asynchronous invocation of AI services, such as Amazon Bedrock or SageMaker.
• Integrate and maintain vector-based retrieval stores to support RAG pipelines for AI inference.
• Build data ingestion and embedding pipelines to ensure vector stores remain synchronized and performant at scale.
• Collaborate with AI engineers to deploy, configure, and optimize models within the application infrastructure.
• Develop CI/CD pipelines using GitHub Actions to ensure frictionless and secure deployments across environments.
• Implement distributed tracing using OpenTelemetry for real-time performance insights and fault isolation.
• Contribute to architectural best practices regarding resilient scaling, low latency, and cost-effective operations.

Department/Project Description

Our client is a forward-thinking leader in the consumer software industry, dedicated to creating intelligent, next-generation digital experiences. The project involves building the backbone of a cloud-native ecosystem designed to power advanced AI-driven features.

As part of this engagement, you will join a high-level engineering team focused on constructing a highly available and horizontally scalable backend platform. This platform supports real-time user interactions and complex, asynchronous AI workloads, including retrieval-augmented generation (RAG) pipelines. This role offers the opportunity to work at the intersection of modern serverless architecture and cutting-edge artificial intelligence, delivering solutions that define the future of intelligent consumer applications.