Senior Software Development Engineer, DC Assistant Development

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help.

You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

About DC Bridge:
Join the DC Bridge team in pioneering next-generation AI/ML solutions that power AWS's global data center operations. We're building cutting-edge systems that orchestrate physical work processes across AWS's worldwide data centers, directly impacting millions of customers who rely on AWS services.

Position Impact:
You'll be at the forefront of transforming data center operations through AI/ML innovations, building the platform primitives that dozens of teams across the Data Center Community build on developing intelligent systems that optimize technician workflows, automate decision-making processes, and enhance operational efficiency across AWS's global infrastructure while enabling AI-powered capabilities for a 30K+ globally distributed user base.

Required Qualifications:
• 7+ years of software development experience with proven expertise in Python, Java, or equivalent languages

Strong background in one or more of the following:

* Generative AI / Agentic Systems LLM orchestration, prompt engineering, RAG architectures, tool-calling patterns, agent frameworks (Strands, LangChain)
* Full-Stack Serverless Engineering AWS Lambda, API Gateway, CloudFront, DynamoDB/RDS, EventBridge, SQS, CDK Infrastructure-as-Code
* Frontend & SDK Development React, TypeScript, Cloudscape Design System, component library design, streaming interfaces (SSE)
* Search & Knowledge Systems OpenSearch/Elasticsearch, vector embeddings, hybrid retrieval, document processing pipelines, semantic chunking
* ML & Data Engineering SageMaker, time-series analysis, anomaly detection, classification models, feature engineering, ETL at scale
* Platform & DevOps CI/CD pipeline design, progressive deployment, synthetic monitoring, observability (CloudWatch, X-Ray, OpenTelemetry)


Ideal Candidate Profile:
• Thrives in ambiguous environments and adapts quickly to change
• Demonstrates a scrappy mindset with ability to deliver results in fast-paced settings
• Maintains deep technical expertise while staying customer-focused
• Shows passionate engagement with AI/ML advancements
• Possesses strong understanding of AI/ML technology application (LLMs, agents, RAG, Skills, ML models)
• Works autonomously and demonstrates deep problem-solving capabilities
• Balances subtle improvements with disruptive innovation when needed

This role offers the opportunity to shape the future of AWS data center operations through innovative AI/ML solutions while working with cutting-edge technologies at unprecedented scale.

Key job responsibilities
• Lead and architect the development of state-of-the-art AI/ML platforms and solutions, serving as a technical leader for both data center operations and engineering teams
• Own end-to-end delivery of technically challenging projects, including scalable ML frameworks, deployment pipelines, and intuitive interfaces for non-ML experts
• Drive operational excellence by building robust data processing pipelines and ETL systems for DC telemetry data, while identifying and addressing operational challenges early
• Mentor and grow junior engineers, acting as a force multiplier by sharing AI/ML expertise and best practices
• Lead cross-functional collaboration efforts to integrate ML solutions into existing DC workflows, while maintaining highest standards for system extensibility and scalability
• Contribute to and champion improvements in development processes, particularly in the context of ML development and deployment
• Provide technical consultation and architectural guidance to internal customers while insisting on the highest standards for long-term system sustainability
• Design and implement reusable components and tools that enhance team productivity and system reliability


About the team
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