Own and build core backend and infrastructure for document intelligence and VLM workflows. Architect, deploy, and scale high-throughput, low-latency production systems; manage deployments, monitoring, reliability, CI/CD, and enterprise cloud/on-prem environments. Turn research prototypes into production and support enterprise deployments.
We are hiring a Founding Software Engineer in San Francisco.
We are building a small, talent-dense team. This role will define the engineering archetype at Unsiloed AI and set the ceiling for the team. We strongly believe technical DNA compounds (or degrades) with every hire and hence the first few matter disproportionately. You will be expected to operate proactively, take full ownership, and independently drive systems from idea to production.
What you Will Do
As a Founding Software Engineer, you will own the entire technical stack end-to-end, from core infrastructure and production systems to deployment, reliability, and developer experience.
- Architect, build, and scale core backend systems powering document intelligence and VLM-based workflows
- Own production infrastructure end-to-end: deployments, monitoring, performance, reliability
- Design and operate high-throughput, low-latency services in real production environments
- Take systems from R&D → production → enterprise scale
- Build and maintain cloud and on-prem deployments (Docker, Kubernetes, Helm) for enterprise customers
- Establish best practices for CI/CD, observability, debugging, and incident response
- Work closely with the founders and research team to turn research prototypes into production-grade, scalable systems.
What We are Looking For
This role is backend & infrastructure-heavy. You should have most of the following:
- Experience building and operating scaled production systems
- Strong backend engineering skills (Python required; C++/Rust is a major plus)
- Experience with distributed systems (microservices, parallel processing, queues, caches like Redis)
- Deep familiarity with cloud infrastructure (AWS, GCP, Azure)
- Hands-on experience with Docker, Kubernetes, Helm, and infrastructure-as-code (Terraform / Pulumi)
- An ownership mindset
- Nice to have: Experience serving ML / VLM / GPU-heavy workloads
Compensation: $150k – $300k
Equity: 0.1% – 1%
Location: In-person, San Francisco
Visa: Open to sponsoring
Hiring process:
We don’t believe interviews alone can assess fit on either side.
Our process centers around paid work trials, which can be done remotely. You will work with us on real problems, collaborate as peers, and get a genuine sense of what building Unsiloed AI feels like.
For any questions, email hiring [at] unsiloed [dot] ai
Similar Jobs
Cloud • Information Technology • Security • Software • Cybersecurity
Design and scale a reusable Customer Success AI platform: build foundational AI infrastructure (orchestration, memory, context, workflow engines), optimize model routing, observability, governance, and security, lead architecture and standards, mentor engineers, and partner cross-functionally to deliver enterprise-grade, multi-product AI capabilities.
Top Skills:
Agentic LoopsAPIsCloud-NativeContext EnginesDistributed SystemsEnterprise MemoryGovernanceKnowledge GraphsLlm OrchestrationMcp ServersMemory ServicesMulti-Agent SystemsObservabilityOrchestration ServicesPlanning SystemsRagSecuritySemantic ModelsState Management FrameworksVector SearchWorkflow Execution Frameworks
Cloud • Information Technology • Security • Software • Cybersecurity
Define vision, strategy, and roadmap for Customer Success AI products. Identify high-impact AI opportunities across workflows, manage products end-to-end from incubation to scale, partner cross-functionally, and drive adoption, measurement, and lifecycle optimization for AI-native employee productivity and operational intelligence.
Top Skills:
Agentic WorkflowsAi AgentsAi PlatformCloud-Native Zero Trust ExchangeGenerative AiLlmsPrompt EngineeringRetrieval-Augmented Generation (Rag)Security Data Lake
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Design, build, and operate cloud-native reliability, release, and test platforms. Integrate test pipelines, observability, and automation into CI/CD and GitOps workflows. Build Kubernetes-based scalable test infrastructure, progressive delivery, chaos/resilience testing, and validation for deployment and operational health. Mentor engineers and drive platform reliability, automation-first solutions, and developer self-service environments.
Top Skills:
AnsibleArgo CdArgo WorkflowsAws EksAzure AksCi/CdCypressFluxGateway ApiGitlab Ci/CdGitopsGoGoogle GkeHelmIngressIstioJavaJunitKubernetesKustomizeLinkerdOpentelemetryPlaywrightPrometheusPytestPythonRest AssuredRubySeleniumTerraformTestng
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine


