Senior Software Engineer, Annapurna Labs

Senior Software Engineer, Annapurna Labs

Job :  |  Services LLC

Annapurna Labs was a startup company acquired by AWS in 2015 and is now fully integrated. Our organization spans silicon engineering, hardware design and verification, software, and operations. We deliver products such as AWS Nitro, ENA, EFA, Graviton, and F1 EC2 Instances, AWS Neuron, Inferentia and Trainium ML Accelerators, and scalable NVMe storage.

Ann2punra Labs Neuron is the complete software stack for the AWS Inferentia and Trainium cloud‑scale machine learning accelerators and the Trn1 and Inf1 servers that use them. This position is for a Senior Software Engineer who will lead the development of machine learning tools to run, optimize, and analyze machine learning workloads. The candidate must have experience leading machine learning tool projects from architecture through several generations of delivery to customers, with deep knowledge of profiling, optimization, resource management, scheduling, and code generation.

Experience with new instruction set architectures (CPU, NPU, GPU, or other compute) is preferred.

• Lead the design, development, and operation of a next‑generation AI workload orchestration platform built on Kubernetes, enabling scalable job scheduling, multi‑node distributed training, and artifact management across custom ML silicon (Inferentia and Trainium families).
• Drive architectural decisions across the full stack—from service APIs and workflow orchestration to cluster‑level scheduling and resource optimization—targeting high availability and hardware utilization.
• Collaborate with ML researchers, SDK developers, hardware design teams, and infrastructure engineers to ensure the platform evolves in lockstep with current and next‑generation AI accelerators.
• Mentor and technically guide a team of software engineers, setting the bar for operational excellence, system design, and developer experience.
• Architect and implement scalable services spanning Kubernetes operators, workflow orchestration, and scheduling algorithms that maximize hardware utilization across a growing fleet of accelerators.
• Translate emerging silicon capabilities into platform features through daily collaboration with researchers, SDK developers, and hardware engineers.
• Own the full lifecycle of systems—from design and implementation through deployment, monitoring, and incident response.
• Improve developer velocity by refining CLI tools, APIs, and framework integrations that reduce friction between writing code and running it at scale.
• Participate in design reviews, code reviews, and operational readiness discussions with a small, high‑ownership team where contributions ship quickly and have immediate customer impact.
• Work in a fast‑paced, startup‑like environment where priorities are driven by the next generation of AI hardware on the roadmap.

Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge‑sharing and mentorship. Senior members provide one‑on‑one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help you develop your engineering expertise so you feel empowered to take on more complex tasks in the future.

AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

• 5+ years of non‑internship professional software development experience
• 5+ years of programming with at least one software programming language
• 5+ years of leading design or architecture of new and existing systems (design patterns, reliability, and scaling)
• 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Experience as a mentor, tech lead, or leading an engineering team