Jobs at aion

Build and maintain core platform services for AION's Compute and Inference platforms. Implement multi-cloud orchestration, resource scheduling, model deployment pipelines, autoscaling, and observability. Develop REST/gRPC services, design DB schemas, integrate message queues and storage, write tests, participate in code reviews, and support production debugging and incident response.

Design, build, and operate Aion's virtualization platform for AI workloads across cloud, hybrid, and on-prem environments. Architect secure, high-performance virtualization infrastructure, implement compute/resource scheduling (CPU, memory, storage, GPU), optimize performance and scaling, automate provisioning and lifecycle management, ensure multi-tenant security and enterprise compliance, and build observability for infrastructure reliability while collaborating with platform and customer teams.

Design and build a scalable orchestration platform and execution engine for enterprise AI workflows. Implement distributed, event-driven systems across Kubernetes, containers, serverless and cloud infrastructure, ensuring reliability, scheduling, retries, observability, and developer-facing APIs/SDKs. Integrate with model serving, data stores, messaging systems, and enterprise services while driving platform reliability and engineering best practices.

Design, build, and operate scalable, secure network infrastructure across cloud and on-premises environments to support AI workloads. Architect hybrid/multi-cloud networking, ensure high availability and security, troubleshoot performance issues, automate provisioning with IaC, and improve observability and disaster recovery. Support customer deployments and incident response.

Design, integrate, validate, and optimize hardware platforms for AI training and inference. Benchmark and troubleshoot server, GPU, networking, and storage performance. Build reliable rack-scale infrastructure, develop validation and diagnostics, support deployments, automate provisioning and monitoring, and collaborate with software, platform, and customer teams to deliver production-ready AI infrastructure.

Lead architecture and delivery of Aion's enterprise AI platform: design scalable, reliable infrastructure; manage and grow engineering teams; drive product delivery, observability, CI/CD, and operational excellence; collaborate cross-functionally and with customers.

Design, build, and deploy production-grade AI applications using LLMs, multimodal models, RAG, and agent frameworks. Integrate AI solutions with enterprise systems, optimize inference pipelines, ensure reliability and observability, and collaborate across product, platform, and customer teams to productionize AI use cases.

Partner with enterprise customers to discover AI opportunities, design end-to-end solution architectures on Aion's platform, lead POC-to-production delivery, integrate with enterprise systems, optimize performance, and provide technical leadership, product feedback, and enablement materials to drive AI adoption.

Design, build, and operate GPU-focused observability and monitoring systems across Kubernetes and bare-metal SLURM clusters. Develop custom exporters, controllers, systemd services, GitOps workflows, and alerting/SLO frameworks; ensure multi-tenant isolation, cost analytics, and automated workload migration to improve GPU utilization and reliability.

Lead and build the People function: design org structure, create scalable hiring/onboarding/performance processes, drive talent development and engagement, ensure multi-region compliance, mentor managers, and improve HR systems to support rapid startup growth.

Lead and execute aion's social media and thought leadership across LinkedIn, X, and other channels. Monitor AI and industry news, create posts, threads, and executive commentary, manage a content calendar, collaborate with design on visuals and video, promote events and speaking engagements, track performance metrics, and build rapid-response systems to capitalize on AI ecosystem developments.

Embed with enterprise customers to discover use cases and build production multimodal agent systems (voice, video, text). Architect RAG and MLOps pipelines, deploy and optimize LLM-powered agents, implement observability and evaluation, and integrate agents into customer systems while advising stakeholders and delivering fast POCs.

Embed with customers to discover use cases, design and build multimodal (voice, video, text) agent systems, implement RAG/vector DB pipelines, deploy and optimize LLMs and agents on aion's platform, instrument observability and evaluation, and advise customers from prototype to production.

Design, build, and own aion's inference platform components (gateway, orchestrator, runtimes, autoscaler). Drive model deployment, rollback, routing, and GPU utilization optimizations. Implement low-latency, high-throughput distributed systems with observability, monitoring, and engineering best practices.

Build and maintain backend platform services for multi-cloud compute and inference, implementing orchestration, resource scheduling, deployment pipelines, autoscaling, APIs, and event-driven systems. Design schemas and service APIs, work with messaging, storage, and databases, ensure quality via testing and observability, participate in design reviews, debug production issues, and document operational runbooks.