The Networking Diagnostics team is seeking a highly motivated and experienced engineer. This person must have hands-on technical expertise to develop critical diagnostic tools for our newest, world-leading networking platforms. This position offers the opportunity to have a real impact in a dynamic, technology-focused company, impacting data centers and high-performance computing (HPC) clusters across the world. We are looking for independent engineers who excel in a fast-paced environment and are passionate about ensuring the stability of next-generation hardware.

What you'll be doing:
Design & Implement: Architect and develop high-performance diagnostic tools and frameworks using Python, tailored for our latest networking platforms.
Performance Optimization: Drive end-to-end development focusing on software that performs efficiently, ensuring diagnostic suites can handle high-throughput data and real-time monitoring without latency.
System Diagnostics: Take charge of developing features that bridge the gap between complex hardware behaviors and software-level diagnostics.
Collaborative Problem Solving: Partner with hardware, firmware, and driver teams to address real-world challenges that demand innovative solutions and a customer-centric approach.
Autonomous Execution: Own the full software development lifecycle of diagnostic features, from initial hardware specification to deployment in dynamic environments.

Key Responsibilities
We are looking for a passionate Software Developer to join our WAF SaaS Platform team, where we build, evolve, and operate our companys cloud-native WAF SaaS product.
In this role, you will develop new SaaS product capabilities while also building and operating the cloud infrastructure that powers the platform. You will work across backend services, Kubernetes environments, automation, CI/CD, monitoring, and, when needed, frontend components.
We are looking for a strong team player with a high sense of ownership, a get-things-done mindset, and the willingness to contribute across all areas of development - from UI and backend to DevOps and cloud infrastructure.
Major Responsibilities
Develop new features and capabilities for our companys WAF SaaS product, with a focus on backend services, cloud infrastructure, and DevOps-oriented development
Design, build, and maintain cloud-native infrastructure that supports customer environments, production workloads, and global SaaS deployments
Take part in creating and operating new POPs, improving customer environment provisioning, and evolving the platforms scalability and availability
Develop SaaS product capabilities such as certificate management, CDN-related flows, DDoS-related capabilities, onboarding flows, and other customer-facing platform features
Work with cloud services, CI/CD pipelines, monitoring, logging, and automation tools
Take end-to-end ownership of features and infrastructure components, from design and implementation through deployment, observability, support, and production operation
Build and maintain dashboards, alerts, and operational tools, using data and metrics to improve reliability, performance, and product decisions
Collaborate closely with developers, DevOps engineers, product managers, security researchers, support teams, and other stakeholders
Support production environments, investigate customer issues, and understand the real-world impact of features, bugs, and infrastructure changes.

As a Senior SDE III on the Elastic Compute team, you work where silicon meets software - your decisions ripple across millions of EC2 instances and shape the performance, security, and cost efficiency of the AWS compute platform. A day might start by root-causing a fleet-wide latency anomaly across the full stack, from the hypervisor and Nitro offload path down to firmware; move into owning the architecture for a multi-year initiative and leading the design review where the hard questions about scale, failure domains, and safe fleet-wide rollout get asked - often co-designed directly with silicon and hardware partners; and end deep in a low-level C/C++ or Rust change, a down-to-the-instruction performance investigation, or twenty minutes pairing with a newer engineer because raising the bar around you is part of the job, not a distraction from it. The systems you build run continuously, at massive scale, with little tolerance for error - so a great day ends with something shipped or a hard problem genuinely understood, knowing your work will be quietly running in data centers around the world tomorrow.

In this role you'll design and build features that shape how customers discover products - tailored to their preferences, helping them find exactly what they need, even before they know they need it. We're defining how LLMs integrate into real-time personalization, how noisy behavioral signals become durable customer understanding, and how AI-powered experiences ship reliably at scale. You'll work across multiple technical teams, ship iteratively, and see your work in the hands of customers quickly. This organization values experimentation, moves fast, and gives engineers real ownership over what they build.

We are looking for a Software Development Engineer with sound technical judgment and a bias for action who takes ownership of problems end to end, communicates clearly, and cares about operational excellence - not just launching features, but making sure they hold up at scale. Someone who naturally raises the bar for the team: mentoring junior developers, advocating engineering best practices, and thinking beyond the immediate sprint.

Key job responsibilities
- Design, build, test, and operate production AI features used by multiple teams and operating at Amazon scale.
- Deliver end-to-end solutions with focus on maintainability, scalability, performance, and reliability.
- Collaborate with Product and Science to define experiences, run experiments, and iterate based on data.
- Build AI-powered experiences including personalized recommendations, relevance explanations, and knowledge-driven features using LLMs and generative AI.
- Define and implement measurement strategies including analytics events and experiment configurations to track engagement and retention.
- Navigate ambiguity and make sound technical decisions in a problem space where established patterns don't always apply.

We are at the forefront of the AI revolution, delivering brand new accelerated compute platforms for global impact. Our Network Architecture group is seeking a talented and motivated Sr. Software Engineer to build the agentic workflows that our architects use in their daily work. The software at the center of this role is our hardware network simulation environment - you will design multi-step agent workflows over it, engineer the context that grounds them in our own specifications and source code, and optimize their runtime performance. If you are passionate about building the practical infrastructure that brings intelligent agents to life, we want to hear from you.


What you'll be doing:
Build agentic workflows - loops, graphs, and multi-step pipelines - that carry real hardware network simulation and analysis work end to end.
Engineer the context these workflows run on, turning our simulation models, specifications, design documents, and source code into context that makes agents accurate in our domain.
Work closely with network architects to understand their workflows and translate them into agent workflows they use daily.
Optimize the runtime performance of our simulation tooling on these platforms, including execution time, compute cost, and end-to-end latency.
Define evaluation and regression testing for agent workflows, so that changes to a prompt, a graph, or a context source are measurable.
Build observability across agent runs: what the agent did, where it failed, and why.
Champion guidelines for secure and reliable agent workflows, including data handling, access control, and interaction boundaries.
Serve as a key technical resource for solving sophisticated integration issues between agents and internal tooling.

We are looking for a strong team player with a high sense of ownership, a "get-things-done" mindset, and the willingness to contribute across all areas of development - from UI and backend to data and detection pipelines.
Major Responsibilities
Develop new features and capabilities for our company's Gen AI Security SaaS product, with a focus on backend services and real-time detection & prevention pipelines
Develop SaaS product capabilities such as prompt-injection and jailbreak detection, content moderation, PII and data-leakage prevention, policy and practice management, and other customer-facing platform features
Contribute to our native inspection agent that runs close to customer traffic
Contribute to the platform's ML pipeline, including data collection and feature engineering that support the platform's detection models
Work with cloud services, CI/CD pipelines, monitoring, logging, and automation tools
Take end-to-end ownership of features, from design and implementation through deployment, observability, support, and production operation
Build and maintain dashboards, alerts, and operational tools, using data and metrics to improve reliability, performance, and product decisions
Collaborate closely with developers, DevOps engineers, product managers, security researchers, support teams, and other stakeholders
Support production environments, investigate customer issues, and understand the real-world impact of features, bugs, and infrastructure changes.

The PerfTech team is looking for a talented C++ Software Engineer to help build the next generation of AI-powered developer tools. You will apply strong C++ and software-engineering fundamentals while gaining hands-on experience with agentic workflows, retrieval systems, and AI services.

In this role, you will contribute to Genie, our company-wide AI knowledge and developer-productivity service. You will work across C++ tools and AI services to help engineers find information, understand complex systems, and work more effectively.

What Youll Be Doing:
Develop production-quality C++ components, APIs, and integrations for our AI-powered developer-tools ecosystem.
Build capabilities connecting native C++ tools with Genies retrieval and agentic features.
Contribute to agentic workflows, retrieval systems, ingestion pipelines, MCP tools, APIs, and enterprise integrations.
Build benchmarks and improve retrieval quality, reliability, performance, and resource usage.
Own features from investigation and design through implementation, testing, and delivery.
Collaborate with graphics, software, and hardware teams developing performance-analysis and developer tools.

We are seeking a highly skilled and versatile Performance Research and Analysis Manager to join our Performance Group. This role will drive end-to-end performance strategy and execution for our next-generation data centers and solutions based on GPU systems, NIC, Switch, DPU and Networking technologies. The ideal candidate will oversee, evaluating, and optimizing end-to-end AI GPU cluster-level performance for scaling out large scale distributed training and inference jobs communication. The role will focus heavily on RDMA, Networking Protocols, Collective Communication, Congestion Control, and Load Balancing algorithms. Secondarily, you will lead our DPUs and Storage technologies for N-S use cases to support AI Inference jobs. Third, you will drive our Performance Dashboards and Observability for cluster-level performance analysis from a stream line telemetry across NICs, Switches, GPUs, and NVlink.

What you'll be doing:

Drive end-to-end performance strategy, characterization, test plans, and optimization for our next-generation AI GPU clusters, focusing on large-scale distributed training and inference workloads.

Deeply evaluate and optimize our Networking core technologies performance, including RDMA/PRDMA, networking protocols, collective communication (NCCL), congestion control, and load-balancing algorithms.

Work on performance research and analysis of our DPUs and storage technologies in North-South (N-S) use cases and deployment scenarios to maximize performance and efficiency for AI inference jobs.

Drive the strategy for performance observability and dashboards across our next-generation data center solutions and supercomputers by leveraging scalable, streamlined telemetry pipelines to build performance dashboards and automated analytics based on real-time performance metrics across NICs, Switches, GPUs, and NVLink boundaries.

Perform deep root-cause analysis (RCA) on complex multi-node performance bottlenecks, driving actionable mitigation plans across hardware, firmware, and software teams.

As the Development Team Lead for HiredScore Sourcing Products, you will manage and mentor a cross-functional team of Full-Stack Engineers, Backend Engineers, and QA Automation Specialists.
Your team's core mission will be to translate AI/ML insights into seamless, scalable features that drive efficiency in recruiter workflows-specifically through resurfacing past applicants, prospects, and internal talent. You will own the entire development lifecycle for your products, from core API implementation to deploying user-facing applications and integration layers (web UIs, RPA/workflows, MS Teams bots)
Key Responsibilities:
Lead, mentor, and grow the diverse engineering team, ensuring effective collaboration between backend, full-stack, and QA functions. Drive best practices in development, code quality, and delivery speed.
Design, document, and oversee the implementation of scalable, reliable, and secure systems, ensuring seamless integration between backend AI services and the user-facing product layers.
Ensure the team maintains a strong quality and automation culture by providing strategic direction to QA specialists and upholding high standards for testing and product stability.
Drive development across the full spectrum of product surfaces: APIs (GraphQL/REST), Web Applications (React/Angular/Vue), and specialized engagement layers.
Ensure efficient consumption of AI outputs by downstream systems, particularly through robust queue-based architectures (like RabbitMQ) and workflow automation (RPA).
Partner closely with Product Management, Data Science, and other engineering teams to translate business requirements into technical execution.

As a System Verification Software Engineer, you will join a unique team that works at the heart of chip development, at the HW/SW boundary, collaborating across teams to ensure our semiconductor platforms meet the highest standards before they reach production, as we lead the market with our cutting-edge devices.
Youll be part of a team that verifies Graviton chips across emulation, silicon, and AWS production fleets-developing the tests, automation, and debug tooling that give us confidence our features function correctly on real hardware.

Key job responsibilities
* Verify and validate Graviton chips in emulation, silicon, and post-production.
* Develop tests that ensure our features function as intended.
* Build automation and debugging tools for silicon regressions and bring-up.
* Collaborate with hardware design and software teams to identify, analyze, and resolve design issues and verification gaps.
* Debug failures across diverse platforms (emulation and silicon).