AWS AI Jobs

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Lead the design and implementation of a scalable, high-availability voice infrastructure that replaces legacy systems. Build and refine multi-threaded server frameworks capable of handling thousands of concurrent, real-time audio streams with minimal jitter and latency. Deploy robust ASR > LLM > TTS pipelines that process thousands of calls concurrently. Develop robust logic for handling media streams, ensuring seamless audio data flow between clients and machine learning models. Build advanced monitoring and load-testing tools specifically designed to simulate high-concurrency voice traffic. Partner with Speech Scientists and Research Engineers to integrate state-of-the-art models into a production-ready environment.

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Drive the architectural vision for the GenerativeAgent product by designing and building a highly scalable, multi-agent platform for real-time voice and text customer service experiences across various industries. Act as a technical authority and advisor for multiple engineering teams, develop system design and technical roadmaps, and define communication, state management, and orchestration patterns for multi-agent systems. Design and implement scalable, multi-tenant deployment architectures, own and define system-level SLOs/SLIs focusing on latency, cost-efficiency, and fault tolerance, identify systemic risks with proactive mitigation strategies, partner with Security and Compliance teams to meet regulatory and security requirements, lead post-incident analysis and improvements, and collaborate cross-functionally with Product, Customer Engineering, Site Reliability Engineering, TPMs, and Research to translate business requirements into system designs and productionize ML research. Mentor senior engineers and communicate complex technical concepts to both technical and non-technical stakeholders.

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The backend developer will own major feature development and work directly with founders on product development from end to end. Responsibilities include working with a small interdisciplinary team across hardware, software, and design to build new products from scratch; building new features and designing new architecture to address challenging problems; building backend infrastructure to perform scalable training in the cloud; rethinking and refactoring existing codebases for scale; and continuously improving and maintaining code in production. The role involves full ownership throughout the entire product lifecycle, including idea generation, design, prototyping, execution, and shipping, contributing to multiple parts of the codebase in various programming languages.

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As a Principal Software Architect at HackerOne, you will define and evolve the architectural vision for the HackerOne Platform and core systems to ensure scalability, reliability, and performance. You will partner with Product, Platform, and Security teams to translate long-term business and product goals into actionable architectural strategies. You will collaborate with Principal and Distinguished Engineers to align on technical direction, establish shared standards, and evolve system design principles. Your role involves leading major cross-team initiatives to modernize architecture, improve observability, and reduce complexity. You will mentor and guide engineering teams to foster technical excellence, knowledge sharing, and continuous improvement. You will evaluate and integrate emerging technologies including AI, GenAI, and LLM-driven architectures to enhance platform intelligence. Additionally, you will drive architectural governance and documentation to ensure maintainability and transparency and communicate architectural direction clearly to technical and non-technical stakeholders. Within the first 30-90 days, you will move from understanding systems and architecture to leading architectural initiatives that impact teams company-wide.

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As an AI Tutor in Coding specializing in Kotlin development, the responsibilities include designing high-quality technical content, examples, and explanations demonstrating best practices in Kotlin development; collaborating with engineers to ensure accuracy and consistency across code samples, tutorials, and developer guides; exploring modern Kotlin frameworks and tools to create practical, real-world examples for learning and testing; and continuously refining content based on feedback, emerging patterns, and advances in the Kotlin ecosystem. The role also involves contributing to projects aligned with skills by creating training prompts and refining model responses to help shape the future of AI while ensuring technology benefits everyone.

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The AI / ML Solutions Engineer at Anyscale is responsible for designing, implementing, and scaling machine learning and AI workloads using Ray and Anyscale directly with customers. This includes implementing production AI / ML workloads such as distributed model training, scalable inference and serving, and data preprocessing and feature pipelines. The role involves working hands-on with customer codebases to refactor or adapt existing workloads to Ray. The engineer advises customers on ML system architecture including application design for distributed execution, resource management and scaling strategies, and reliability, fault tolerance, and performance tuning. They guide customers through architectural and operational changes needed to adopt Ray and Anyscale effectively. Additionally, the engineer partners with customer MLE and MLOps teams to integrate Ray into existing platforms and workflows, supports CI/CD, monitoring, retraining, and operational best practices, and helps customers transition from experimentation to production-grade ML systems. They also enable customer teams through working sessions, design reviews, training delivery, and hands-on guidance, contribute feedback to product, engineering, and education teams, and help develop reference architectures, examples, and best practices based on real customer use cases.

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As a Software Engineer on the Codex for Teams team, you will be responsible for shaping the evolution of Codex by identifying how teams actually use and sometimes break AI-powered software engineering tools, driving changes across product, infrastructure, and model behavior to make Codex a reliable teammate for organizations. You will build core team and enterprise primitives that enable Codex to scale, including role-based access control (RBAC), admin and audit surfaces, usage and rate limits, pricing controls, managed configuration and constraints, and analytics for deep visibility into Codex usage. You will design and own secure, observable, full-stack systems that power Codex across web, IDEs, CLI, and CI/CD environments, integrating with enterprise identity and governance systems (SSO/SAML/OIDC, SCIM, policy enforcement) and developing data-access patterns that are performant, compliant, and trustworthy. The role involves leading real-world deployments and launches by working directly with customers and the Go To Market team to roll out Codex, using live usage and operational feedback to rapidly iterate and improve the product and platform capabilities. This position owns systems end-to-end, from architecture and implementation to production operations, emphasizing quality and velocity.

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The Solutions Engineer (AI/ML, Pre-Sales) will work closely with strategic customers to understand their data curation needs, business challenges, and technical requirements. The role involves leading end-to-end customer proofs of concept (PoCs) that connect data curation to training behavior and evaluation outcomes, including dataset analysis, training plan design, and interpreting results. They will partner with customer machine learning teams to map data and curation strategies, design and execute evaluation plans for base and post-trained models, select appropriate benchmarks and metrics, and run model evaluations. Additionally, the engineer will produce customer-ready evaluation reports detailing methodology, metrics, baselines, ablations (e.g., curated vs raw data), conclusions, and recommendations for productionization. They must communicate technical results effectively to both ML experts and executive stakeholders, explaining tradeoffs in compute, latency, and deployment cost. Collaboration with go-to-market, engineering, and research teams is essential to deliver compelling demos, align on requirements, and incorporate customer insights into model training and product strategies. The role also includes providing technical guidance, training, and documentation to enable prospects to confidently assess the solution.

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As a Software Engineer working on AI systems, responsibilities include playing a foundational role in research, experimentation, and rapid improvement of AI systems to build a capable, reliable AI automation platform used worldwide in mission critical production environments. Tasks involve designing experiments and testing ideas to optimize key internal AI benchmarks, designing and improving evaluation frameworks to accelerate experimentation speed and direction, training, fine-tuning, and optimizing machine learning models, performing rigorous evaluation and testing for model accuracy, generalization, and performance, collaborating and contributing to core product development to enhance platform capabilities, and setting up observability and monitoring systems to safety check model behavior in critical settings.

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As a Full-Stack Software Engineer on the Security Products team, you will build, deploy, and maintain applications and systems that bring advanced AI-driven security capabilities to real users. You will work directly with internal and external customers to understand their workflows and translate them into intuitive, powerful product experiences. Your responsibilities include designing and building efficient and reusable frontend systems that support complex web applications, planning and deploying frontend infrastructure necessary for building, testing, and deploying products, collaborating across OpenAI’s product, research, engineering, and security organizations to maximize impact, and helping to shape the engineering culture, architecture, and processes of this new business unit.