--- title: 'Full Stack Engineer at zaimler' canonical: 'https://feeny.ai/job/full-stack-engineer-zaimler-san-mateo-bakhw51wsntp' type: 'job' last_seen: '2026-09-08' --- # Full Stack Engineer at zaimler - **Company:** zaimler - **Location:** San Mateo, CA - **Employment:** full-time - **Work type:** onsite - **Posted:** 2025-12-04 - **Last confirmed live:** 2026-09-08 - **Apply:** https://jobs.lever.co/zaimler/eeec3f5d-b1e4-4d3b-b603-d5fdb1540ed8 ## Job description ## About zaimler AI agents can't reason over data they don't understand. Enterprise data today is fragmented across dozens of systems with no shared context, meaning, or structure, and that's why most enterprise AI is failing. The shift from copilots to autonomous agents is creating an entirely new infrastructure layer, and we're building it. zaimler is the context infrastructure for the agentic era: a platform that automatically discovers domain knowledge, maps relationships, and gives AI agents the semantic understanding to operate with precision at scale. Imagine knowledge graphs that support real-time inference, built for systems that need to reason, not just retrieve. zaimler was founded by Biswajit Das (ex-VP Engineering, Truera), a Data Infra veteran and former Chief Architect at Visa, and Sofus Macskassy (ex-Director of Engineering, LinkedIn), who built one of the largest knowledge graphs in production in the industry at LinkedIn. We're growing and deploying with major enterprises across insurance, travel, and technology. If you want to build infrastructure that the next decade of enterprise AI runs on, we'd love to talk. ## Why this role exists Our platform is used by engineers, and engineers judge infrastructure by how fast it stops confusing them. We have a hard system underneath: graphs, real-time inference, agent behavior in production. Today, understanding it takes a conversation with us. That's a ceiling on how fast we grow. This role exists to remove it, by owning the surface where customers actually meet the product and making it obvious. ## The role You'll own product surface end to end: the interfaces, the APIs behind them, and the data models underneath. The hard part isn't the CRUD. It's making genuinely complex system behavior legible and fast for the people using it. That takes taste as much as it takes engineering. The split is roughly [60% frontend and API layer, 40% backend services]. You will not be handed a design file, and you will not be handed a spec. If you want to go deep on distributed systems and never touch a UI, this is the wrong role. If you can't hold your own on the backend either, it's also the wrong role. We're small and senior. You'll pick the architecture, ship it, watch it in production, and fix what's wrong. ## What you'll do - Ship features across the whole stack. React and TypeScript on top, Python or Go underneath, real data models in between - Talk to customers directly. Join calls, watch people use what you built, and ship against what you learn - Sit with platform, data, and ML engineers to figure out what the system can do, then design a product experience around it - Take things from idea to production, including the testing, deploys, monitoring, and the second version after you learn you got it wrong - Sharpen the APIs, tooling, and UI patterns so the platform stops needing explanation What success looks like - First few weeks: You've shipped something real to production and sat in on a customer call - First few months: You own a major surface of the product outright, and you're the person who decides how it's built - Beyond: The platform is noticeably easier to understand than when you arrived, and you're raising the bar on how everyone here ships ## What we're looking for We care about what you've built, not how long you've been building. - You've shipped production software end to end and can point at something and say "I built that" - You're strong on the backend (Python, Go, Java, or similar) and can build a real React/TypeScript app without waiting for a designer - You have opinions about API design and data modeling, and can defend them - You've operated things in the cloud (AWS, GCP, or Azure) and debugged them at 11pm - You make pragmatic calls under ambiguity and know which tradeoffs are worth the argument - You want to be near customers, not shielded from them Helps, doesn't gate: data-heavy or developer-facing products, distributed systems, ML-adjacent platforms, Kubernetes, observability and performance work, a real interest in AI infrastructure. ## Why Join - Meaningful equity. You're early. The scope and the upside both reflect that. - The infrastructure layer for agentic AI is being built right now. Very few people get to work on a layer this foundational this early. - Small, senior team. Your scope is as large as you're willing to make it. - Real ownership of both architecture and product direction, not a ticket queue. - Full benefits (medical, dental, vision, 401k). We sponsor H-1B visas and help with immigration. Apply Send us (what you've built: a repo, a product, a thing you shipped that you're proud of) at caleb@zaimler.ai. Tell us what was hard about it. We value builders over résumés. If this role excites you but you don't check every box, apply anyway and show us the work. We value builders over résumés. If this role excites you but you don't check every box, we still want to hear from you. zaimler is an equal opportunity employer. ## About zaimler ## Company Overview - **One-liner**: zaimler provides a unified data context and governance layer that enables enterprises to build deterministic AI agents by curating siloed data into a live, governed ontology. - **Entity Type**: Private (Seed stage; raised $10M) - **Headquarters**: San Mateo, California, USA - **Founded**: 2024 - **Founders**: Not publicly named (described as industry veterans with experience in data infrastructure and ML research) ## Core Business - **Primary industry/industries**: Data Infrastructure & Analytics, Enterprise AI - **Target customers**: B2B – large enterprises in insurance, travel, healthcare, and technology sectors - **Mission or purpose statement**: “Make your data AI ready” – one governed model over existing data, serving every agent, analyst, and application. ## Products & Services - **Platform**: The context and governance layer for agentic AI. Connects sources (ODS, lakehouses, systems of record), maps a unified model, and serves every workload from one foundation. - **Ontology**: Auto-inferred by a semantic analyzer, validated by the team. Reduces ontology-building from quarters to days. - **Explorer**: Natural-language query interface that traces every answer back to its source across all connected systems. - **Governance**: Single control plane for policy, lineage, and audit. Enforces access policies across every source without moving data. ## Market Standing - **Valuation/Market Cap**: Not disclosed (Seed stage, raised $10M) - **Key Metric**: Total funding of $10M (Seed round); signing 7-figure contracts with early enterprise customers. - **Notable Investors/Partners**: Not explicitly named in available sources; investors are likely venture firms (undisclosed). - **Growth Signals**: Team grew from 1 to ~12 employees (+150% YoY according to LinkedIn, though likely undercounted); hiring pace of 3 roles per 90 days; has significant traction with large contracts. ## Competitive Advantages - **Auto-inferred ontology**: Uses semantic analysis to automatically map business concepts, replacing manual, quarter-long ontology builds. - **Sovereign deployment**: Supports VPC, air-gapped, or on-prem deployments – critical for regulated industries. - **Real-time context update**: Changes in source systems are reflected live without data movement. - **Unified governance**: Access policies enforced from a single point of entry across all sources. ## Strategic Focus - **Current priorities**: Scaling the platform to serve more enterprise workloads; expanding go-to-market in insurance, healthcare, and travel verticals; building out the engineering team (Data Infrastructure Engineer, Forward Deployed Engineer, BI Engineer). - **Direction**: Becoming the standard infrastructure layer for agentic AI – enabling autonomous agents to reason over fragmented enterprise data with precision and trust. ## Why Work Here - **Culture**: Lean, high-impact team of 12-50 people with deep expertise in data infrastructure and ML research. Emphasis on solving hard problems for enterprise AI. - **Remote/Hybrid/Office**: Hybrid and on-site options depending on role: - San Mateo, CA – On-site (Data Infrastructure Engineer) - London, UK – Hybrid (Forward Deployed Engineer) - Bengaluru, India – On-site (BI Engineer) - **Notable perks**: Not detailed in sources, but working at an early-stage, well-funded AI infrastructure startup with proven founder pedigree and large customer traction offers significant equity upside and ownership. ## Sources 1. [zaimler.ai](https://zaimler.ai/) 2. [jobs.lever.co/zaimler](https://jobs.lever.co/zaimler) 3. [linkedin.com/company/zaimler](https://linkedin.com/company/zaimler) 4. [builtin.com/company/zaimler](https://builtin.com/company/zaimler) 5. [getclera.com/companies/zaimler-ai](https://www.getclera.com/companies/zaimler-ai) ## Other roles at zaimler - [Forward Deployed Engineer](https://feeny.ai/job/forward-deployed-engineer-zaimler-london-bmnf4zwdetry) — London, United Kingdom - [Data Infrastructure Engineer (Query Engine)](https://feeny.ai/job/data-infrastructure-engineer-query-engine-zaimler-san-mateo-0v41r43srxm3) — San Mateo, CA - [BI Integration Engineer](https://feeny.ai/job/bi-integration-engineer-zaimler-bengaluru-e17pw5jbaxff) — Bengaluru, India - [Director of Marketing](https://feeny.ai/job/director-of-marketing-zaimler-san-mateo-nw9fjrradncn) — San Mateo, CA - [Head of Product](https://feeny.ai/job/head-of-product-zaimler-san-mateo-fm34fzygn69c) — San Mateo, CA - [Software Engineer in Test](https://feeny.ai/job/software-engineer-in-test-zaimler-bengaluru-vpb8vwf80z2g) — Bengaluru, India - [Senior Security Engineer](https://feeny.ai/job/senior-security-engineer-zaimler-bengaluru-88fze44c7c21) — Bengaluru, India - [Backend Engineer](https://feeny.ai/job/backend-engineer-zaimler-bengaluru-ddk4wnsf4vkj) — Bengaluru, India - [Cloud Infrastructure Engineer](https://feeny.ai/job/cloud-infrastructure-engineer-zaimler-bengaluru-hmf5pzhkerg9) — Bengaluru, India - [ML Infrastructure Engineer](https://feeny.ai/job/ml-infrastructure-engineer-zaimler-san-mateo-vtjvm5effrqe) — San Mateo, CA