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Senior Engineering Manager - Accelerated Compute Memory Systems

2 hours, 31 minutes ago
United States
Full-time
Lead
Infrastructure Engineer
DevOps and Infrastructure
Apache Airflow AWS Azure C++ CloudFormation Datadog GCP Go Grafana Java Kafka Kubeflow Kubernetes Machine Learning NLP Prometheus Pulumi Python PyTorch RabbitMQ Rust TensorFlow Terraform
Apply Now
Pryon

Pryon

Pryon delivers instant AI-powered answers from enterprise content, improving productivity and enhancing customer experiences.

Internet Software & Services
51-250
Founded 2017
$159M raised
View All Jobs 9

Description

  • Build and lead a team delivering cloud-native ingestion, retrieval, and inference layers for mission-critical deployments.
  • Architect and deliver scalable, fault-tolerant distributed systems for billions of documents and burst traffic at 30K+ concurrent users.
  • Guide implementation of multimodal ingestion pipelines for formats including PDF, HTML, DOCX, JSON, XML, PPTX, and TIFF.
  • Oversee design and optimization of LLM-driven ingestion and retrieval workflows using modern orchestration frameworks.
  • Own performance tuning for high-throughput, low-latency production environments through async orchestration and resource management.
  • Establish benchmarking, compliance, and automated testing strategies for petabyte-scale systems.
  • Lead architecture decisions at the application and service layer while mentoring and scaling a high-performing engineering team.
  • Collaborate cross-functionally with Product, Executive Leadership, Customer Success, Research, AI/ML Engineering, and Platform teams.

Requirements

  • 10+ years of software engineering experience and 5+ years in management roles delivering large-scale AI/ML systems and cloud infrastructure.
  • Expert-level proficiency in Python and strong experience in at least one systems language such as Go, Rust, C++, or Java.
  • 5+ years building production-grade distributed systems on cloud platforms such as AWS, GCP, or Azure.
  • Hands-on experience with modern ML orchestration frameworks such as Ray, Kubeflow, Airflow, or similar tools.
  • Production experience with vector databases such as Pinecone, Weaviate, Qdrant, or Milvus.
  • Deep understanding of message queuing and streaming systems such as Kafka, Pulsar, RabbitMQ, or Kinesis.
  • Experience optimizing LLM inference and retrieval workloads at the application or framework level, such as with PyTorch, TensorFlow, or vLLM.
  • Experience with cloud-native distributed systems architecture, including Kubernetes/EKS/GKE, storage, networking, observability, security, disaster recovery, and cost optimization.
  • Experience with infrastructure-as-code and DevOps tools such as Terraform, CloudFormation, or Pulumi, plus distributed tracing, metrics, and logging tools such as Datadog, Prometheus, Grafana, or CloudWatch.
  • Experience with parallel programming models, custom hardware accelerators or bare-metal cluster management, or on-premises datacenter/HPC operations tools such as Slurm.
  • Direct experience building multimodal ingestion pipelines for knowledge management platforms.
  • Previous success managing engineering teams delivering production-scale AI infrastructure in startup or high-growth environments.
  • Strong communication skills and the ability to translate technical decisions for executive and product stakeholders.
  • Comfort with startup dynamics, rapid iteration, evolving requirements, and wearing multiple hats.
  • Authorized to work in the United States; the company cannot sponsor or transfer work visas at this time.

Benefits

  • $220,000 to $250,000 annual salary.
  • Remote-first organization.
  • 100% company-paid health, dental, and vision insurance for employees and dependents.
  • Life insurance, short-term disability, and long-term disability coverage.
  • 401(k) retirement plan.
  • Unlimited PTO.

Interested in this position?

Apply directly on the company website

Apply Now

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