Kisi Incorporated Filial jobb

About the role The Firmware Developer designs, builds and owns the firmware that runs on Kisi's access control hardware, from readers and controllers to video intercoms and wireless locks. Rather than shipping code and moving on, the role makes sure every device in our remotely managed worldwide fleet is secure, reliable and updatable, and that new products and features reach customers on quality. Responsibilities Firmware development. Write and maintain robust firmware for current and future Kisi products on an industrial-strength embedded platform with built-in support for secure boot and OTA updates. Testing and fleet rollout. Define rigorous acceptance tests and, together with our QA engineers, supervise the rollout of new products and features to our global fleet of connected devices. Factory automation. Improve the efficiency of factory processes by automating flows such as quality assurance, device registration and labeling, so every device ships on quality. Security and reliability. Build firmware with security at its core, from secure boot and encrypted communication to safe OTA updates and recovery, so our devices can be trusted in the field. Platform selection. Take part in evaluating and selecting our next-generation IoT platform provider against strict security and business continuity requirements. Cross-functional collaboration. Work closely with hardware, cloud, mobile and support teams to diagnose field issues, improve device performance and shape the product roadmap. Success looks like: Kisi devices around the world run secure, reliable firmware, updates ship smoothly, and new products reach customers on time and on quality. Qualifications Strong proficiency in C for embedded systems Experience with microcontroller architectures (e.g. ARM Cortex-M) and peripheral interfaces such as SPI, I2C and UART Experience with real-time operating systems (e.g. FreeRTOS) Hands-on experience with embedded development tools such as J-Link, ST-Link, ARM-GCC and gdb, plus software tools like Git, Make/CMake and Python Understanding of secure boot, OTA updates and device security best practices Basic knowledge of assembly and Embedded Linux is a plus Excellent communication and teamwork skills, with the ability to own goals and see them through

About the role The Analytics Engineer designs, builds and owns Kisi's trusted, AI-ready data and insights layer. Rather than fielding individual data requests, the role makes sure that people and AI tools across the company get correct, authorized and context-aware answers on their own, and measures how accurate and impactful those answers are. Responsibilities Data activation in operational tools. Deliver relevant, trusted data into the tools each team already uses (e.g. enriching HubSpot with data from Stripe, Chargebee, the Kisi API and other sources) so teams can act without requesting reports. Trusted insights layer. Build and maintain a documented, semantically modeled layer that humans and AI can query for accurate answers. Encode business context (such as the Stripe to Chargebee migration) and surface known data-quality limitations alongside results. Consolidation of reporting assets. Migrate existing dashboards, reports and connected Sheets onto the insights layer to create a single source of truth. Self-serve audiences and ad-hoc requests. Enable teams to build targeted audiences and one-off data pulls themselves, including through AI tools, and handle remaining business requests as they arise. Source coverage. Integrate the business data sources needed for complete insights, such as Google Analytics, Facebook Ads and other marketing platforms. Data governance and access control. Ensure every consumer, human or AI, can only access data they are authorized to see, with role-based access across the insights layer, dashboards and AI integrations. Quality and impact measurement. Maintain an accuracy benchmark of known-correct figures and track adoption, time saved and decisions supported. Success looks like: Team members get the insights they need, right when they need them, and trust them. Qualifications Strong SQL and data modeling skills, including dimensional or semantic modeling in a cloud warehouse (BigQuery or similar) Experience building and maintaining data pipelines and integrations with SaaS tools such as HubSpot, Stripe and Chargebee Experience making data usable by AI tools and LLMs, including documentation, semantic layers and guardrails Working knowledge of data governance and role-based access control Ability to translate business questions into durable data products and to explain data limitations clearly to non-technical stakeholders