At Sylogic, we're on a mission to revolutionize infrastructure automation through artificial intelligence. We are a stealth startup headquartered in Silicon Valley and are funded by Tier 1 VCs. We are a passionate team that is solving complex AI challenges from the ground up. We seek founding peers with high intelligence, intellectual honesty and personal agency.

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Responsibilities:

• Develop a high throughput backend for deploying AI Agents in self hosted and SaaS offerings
• Manage data storage, retrieval and processing for AI training and inference
• Simplify and streamline the production and deployment process 
• Collaborate with other technical peers (esp. Front end Developers, Machine Learning Developers, DevOps, SREs, sales engineers, specialized contractors and industry experts)
• Collect feedback from engineers, product managers and sales leads to plan release milestones
• Empathetically work with enterprise customers to alleviate their pain

You may be a good fit if you:

• Advocate and practice strong engineering fundamentals (esp. code quality, automated white box and black box testing, meet SLAs for latency & throughput, simplified architecture, API security, traceable logging, peer reviews)
• Have built scaled backends for complex applications on different platforms. In particular, experience with a few of these technologies and practices are helpful:
  
  • Python backends using front end frameworks such as Flask while using shared memory and message passing mechanisms in low latency scenarios
  • Modular microservices deployed with containers
  • Mature telemetry with custom signals and profiled performance
• Managed large data volumes at high throughput using databases (we use Postgres and MongoDB) and custom ETL pipelines
• Are familiar or experienced with DevOps and SRE practices including CI/CD, self hosted and SaaS deployments and VM instance management

Strong candidates may also have: 

• Built distributed computing platforms for background jobs and live workloads using frameworks such as Ray and Kubernetes
• Experience developing scaled ML systems in collaboration with ML Engineers
• Worked in cloud environments while building internal developer platforms
• Experience with architecting and building secure systems 

Qualifications, logistics and traits:

• Bachelor’s, Master’s or a Ph.D. in Computer Science, Mathematics or fundamental sciences
• Lives in the Bay Area or is willing to relocate here upon employment
• Work with peers at the office at least 3 days a week
• Organized and detail oriented person who is comfortable and nimble with ambiguity. Has the mindset to learn and to figure things out by doing. Is adaptable and eager to learn new technologies and tools.

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