Top Tech Jobs & Startup Jobs

Build and operate core data infrastructure for edge and hybrid environments, including ingestion, OT/IoT integrations, real-time streaming, data contracts, schemas, validation, lineage, observability, telemetry, and scalable query access. The role requires production ownership, reliability practices, customer integration, and collaboration across engineering and customer-facing teams. Candidates should have 6+ years of experience with production data, streaming, or integration systems and proficiency in Python and/or Go.

Build and own the company’s iOS mobile application from the ground up, with Android planned next. Develop mobile UX, integrate authentication, payments, databases, APIs, and existing AI technology, and contribute across the backend when needed. Translate designs into polished production code, ship rapidly, iterate using user feedback and data, and establish mobile engineering practices. Collaborate closely with engineering, product, and design in a fast-paced, in-office startup environment.

Build and scale a permitting platform using React, Remix, TypeScript, Prisma, PostgreSQL, and AWS. Collaborate with customers and teammates, shape product direction and architecture, ship frequently, and establish engineering practices. The role emphasizes product-minded development, user empathy, clear communication, rapid delivery, and experimentation with AI-assisted workflows. Candidates should have at least two years of professional full-stack product development experience and be based on the West Coast, preferably in the San Francisco Bay Area.

Build and maintain scalable UI, API, and backend test automation using Python, Robot Framework, Playwright, and Selenium. Integrate testing into Jenkins and CI/CD pipelines, develop Page Object Model scenarios, analyze quality metrics, and improve software reliability. Collaborate with engineering, architecture, product, and UX teams; mentor junior QA engineers; and use AI-assisted tools safely for test generation and maintenance. The role is remote and requires no regular travel.

Provides expert technical guidance to customers adopting and scaling cloud-native platforms. Responsibilities include architectural advising, platform implementation support, troubleshooting distributed systems, reviewing code, collaborating with engineering and sales teams, contributing to open-source projects, and maintaining strong customer relationships. The role requires Kubernetes experience, programming knowledge, technical communication skills, and empathy in high-pressure support situations.

Own end-to-end customer deployments of AI and edge platforms across hardware, networking, sensors, data systems, and applications. Integrate customer OT/IT environments, diagnose cross-stack production issues, build deployment tooling, and translate field learnings into repeatable patterns and product improvements. The role requires strong engineering judgment, customer collaboration, autonomy, and 25–50% travel.

Define scalable deployment patterns, playbooks, success frameworks, and KPIs that improve customer ROI, adoption, time-to-value, and repeatability. Advise customer and partner executives, lead deployments, identify delivery friction, and collaborate with engineering, product, field, and commercial teams. Create field-grounded blogs, white papers, use cases, customer stories, and enablement materials using AI tools. The role requires 25–50% travel and strong technical fluency across infrastructure, security, networking, data systems, and applied AI.

Build and operate production-grade private AI platform capabilities, including agentic and multi-agent workflows, orchestration, evaluation, monitoring, fine-tuning, runtime optimization, safety controls, APIs, and rollback mechanisms. Partner with data and infrastructure teams to improve reliability, performance, and deployment quality. Senior engineers also mentor teammates, review designs, and lead major platform components.