--- title: 'Software Engineer in Test at zaimler' canonical: 'https://feeny.ai/job/software-engineer-in-test-zaimler-bengaluru-vpb8vwf80z2g' type: 'job' last_seen: '2026-09-08' --- # Software Engineer in Test at zaimler - **Company:** zaimler - **Location:** Bengaluru, India - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-02-06 - **Last confirmed live:** 2026-09-08 - **Apply:** https://jobs.lever.co/zaimler/119feb40-9fc7-474b-9ea4-089e39f5e861 ## 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. ## The Role We're looking for a Software Engineer in Test to own the quality and reliability of zaimler's platform from the ground up. Our infrastructure handles real-time knowledge graph construction, semantic inference, and data ingestion across complex enterprise environments, systems where correctness isn't optional and failures are expensive. You'll build the testing infrastructure, performance benchmarks, and integration validation that let us ship with confidence as we scale across production deployments. This is not a QA role. You'll write more code than most software engineers, and the systems you build will be as critical as the platform itself. ## What You'll Do - Design and build end-to-end test infrastructure for zaimler's backend services, APIs, and data pipelines - Own performance and load testing: define benchmarks, build harnesses, and establish baselines for latency, throughput, and resource consumption under production-realistic conditions - Build and maintain integration test suites that validate correctness across the full stack, from data ingestion through knowledge graph construction to inference endpoints - Develop automated regression and smoke test pipelines integrated into CI/CD, ensuring every deploy is validated before it reaches enterprise customers - Identify reliability risks early by instrumenting systems, analyzing failure modes, and building chaos/fault-injection tests for critical paths - Collaborate directly with infrastructure and ML engineers to define testability requirements for new systems before they're built, not after Must-haves: - 3+ years of experience in software engineering, test engineering, or a related role - Strong software engineering fundamentals: you write production-grade code, not just test scripts - Deep experience with backend and API testing: REST/gRPC, async workflows, distributed systems - Hands-on experience building performance and load testing frameworks (e.g., Locust, k6, Gatling, or custom tooling) - Proficiency in Python; familiarity with Go or Java is a plus - Experience with CI/CD pipelines (GitHub Actions, Jenkins, or similar) and containerized environments (Docker, Kubernetes) - Understanding of data pipeline testing, validating correctness, consistency, and completeness across ETL or streaming systems Nice-to-haves: - Experience testing graph databases, knowledge graphs, or semantic/ML inference systems - Familiarity with observability tooling (Prometheus, Grafana, Datadog) and using metrics to drive test strategy - Background in infrastructure-as-code and environment provisioning for test environments - Experience at a startup or early-stage company where you built testing practices from scratch Working style: - You care about quality as a property of the system, not a phase in the process - You're comfortable defining what "good" looks like when there's no existing playbook - You'd rather automate yourself out of repetitive work than do it twice ## Compensation & Benefits - Competitive salary benchmarked to the Bengaluru market - Meaningful early-stage equity - Health insurance - Flexible PTO - On-site in Bengaluru 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. 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 - [Senior Security Engineer](https://feeny.ai/job/senior-security-engineer-zaimler-bengaluru-88fze44c7c21) — Bengaluru, India - [Full Stack Engineer](https://feeny.ai/job/full-stack-engineer-zaimler-san-mateo-bakhw51wsntp) — San Mateo, CA - [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