> Markdown version of [/jobs/ext/2863110-software-engineering-manager-search](https://www.wearedevelopers.com/jobs/ext/2863110-software-engineering-manager-search). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineering Manager - Search - **Company:** Verkada Inc. - **Location:** San Mateo, CA, United States - **Experience:** Experienced - **Salary:** $200,000.0 - $315,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Computer Vision, C++ (Programming Language), Code Coverage, Databases, Continuous Integration, Distributed Systems, Firmware, Apache POI, Information Retrieval, Python (Programming Language), Machine Learning, Open Source Technology, Recommender Systems, Search Technologies, Software Engineering, Load Balancing, Delivery Pipeline, Large Language Models, Model Validation, Generative AI, Backend, Integration Tests, Apache Kafka, Search Engines, Machine Learning Operations, Front End Software Development, Image Search - **Published:** September 12, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/16721226?backUrl=%2Fcareer%2F16721226%2FSoftware-Engineering-Manager-Search-California-San-Mateo ## About the Role * 7+ years of software engineering experience, including 2+ years managing backend or ML engineering teams. * Track record leading 5+ engineers running production services at meaningful scale. * 4+ years of hands-on experience in at least two of: information retrieval, vector / embeddings-based search, computer vision, or large-scale recommendation systems. * 2+ years productionizing modern LLMs, VLMs, or agentic systems (evals, guardrails, latency/cost tuning). * Deep proficiency in Python plus Go/Java/C++; fluent in distributed systems (gRPC, Kafka) and a major cloud provider (AWS preferred). Hands-on with at least one production vector database or search engine (OpenSearch, Turbopuffer, FAISS, Milvus, pgvector, etc.). * Strong operational instincts: on-call ownership, post-mortem rigor, and a habit of defining metrics and building evals to drive quality on high-availability services. Nice to Haves * Experience integrating foundation models via open-source GPU inference stacks. * Familiarity with face recognition, person re-identification, LPR, or similar fine-grained CV pipelines. * Background in physical security, video surveillance, or IoT/connected-device domains. * CI/CD experience for ML/search services. ## Description We are hiring an Engineering Manager to lead Verkada's Search team, the group responsible for the AI-powered search and computer vision capabilities that make our camera fleet best in class in investigation and alerting. From face and person search to license plate recognition, reverse image search, and our next generation of LLM- and VLM-powered agentic experiences, the Search team owns the backend systems that let our customers find what they need across billions of frames in seconds. As the leader of this team you will not just be managing engineers; you will be setting the technical direction for how Verkada defines search with embedding-based retrieval all to an agentic, multi-modal experience powered by modern LLMs and VLMs. You will own a portfolio of production services (API, inference pipelines, vector databases, etc.), drive active migrations, and hire, mentor, and scale a team of backend, frontend, and ML engineers to execute against an ambitious product roadmap while raising the bar on reliability, latency, and cost. What You'll Do Leadership & Team Building * Build the Team: Recruit, hire, and mentor a high-performing group of backend and ML engineers covering search infrastructure, computer vision, and applied AI. * Strategic Oversight: Own the end-to-end roadmap for Search and ML engineering backend from product-facing features like POI, LPR, and AI Search to the platform services that power them. * Cross-Functional Partnership: Partner closely with Product, Design, CV/ML research, Camera Firmware, and Infrastructure teams to align on priorities, dependencies, and deployment plans. AI Search & Applied ML (Hands-On) * Agentic & Generative AI: Drive the rollout of AI-Powered Search, LLM migrations, VLM experimentation, and agentic AI into production-grade features. * Embeddings & Retrieval: Oversee the evolution of our vector search stack to improve recall, latency, and cost at fleet scale. * Model Evaluation: Lead detection evaluation, model consistency, and ongoing quality improvements for various CV and ML pipelines. Search Infrastructure & Platform * Service Ownership: Accountable for a portfolio of production services including submission endpoints, inference pipelines, APIs and database layer. * Migrations & Deprecations: Execute in-flight migrations into new advanced pipelines and deprecations of old pipelines without disrupting customer-facing features. * Scalability & Performance: Drive large-org optimizations, inference engine stability, gRPC load balancing, and connection-hardening work to keep the pipeline healthy as the fleet grows. Reliability & Quality * On-Call & Incident Response: Own the team on-call rotation, post-mortem quality, and the new programs required to scale the team. * Test Coverage: Expand integration test coverage and search pipeline change testing to catch regressions before they reach production. * Telemetry & Dashboards: Define and track the metrics that matter (e.g. API latency, search quality, inference stability, field reliability, etc.) via dashboards and service SLOs. ## Related Videos - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Playing Pong on a shoulder press machine](https://www.wearedevelopers.com/videos/100140-playing-pong-on-a-shoulder-press-machine) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Tomb rAIder: AI Search with Kotlin](https://www.wearedevelopers.com/videos/1989-tomb-raider-ai-search-with-kotlin) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Agent Smith Gets Hardware: Autonomous IoT Hacking From Debug Port to Cloud API](https://www.wearedevelopers.com/videos/100258-agent-smith-gets-hardware-autonomous-iot-hacking-from-debug-port-to-cloud-api) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Where To Find Software Engineering Jobs](https://www.wearedevelopers.com/magazine/396-where-to-find-software-engineering-jobs) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Is Software Engineering Over-Saturated?](https://www.wearedevelopers.com/magazine/418-is-software-engineering-over-saturated) - [Find a Developer Job: 12 Best Job Sites For Developers](https://www.wearedevelopers.com/magazine/165-find-a-developer-job-12-best-job-sites-for-developers) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)