# Full Stack Developer **Company:** [Teserac, Inc.](https://jobs.workable.com/companies/5M5Hqem4UeMobhASgUE8TD.md) **Location:** Santa Clara, United States **Workplace:** hybrid **Employment type:** Full-time [Apply for this job](https://jobs.workable.com/view/97f6a0eb-030f-45b5-b233-1e2bdb3b85e0) ## Description **About the Role** Data centers run on thousands of sensors, meters, and control systems, and the teams who run their power infrastructure have to make sense of all of it in real time. Teserac is building Neuron™, an AI-native observability and automation platform that gives those teams full visibility into their power operations and helps them get ahead of problems. At its core is an AI teammate that works alongside every operator around the clock: detecting anomalies, correlating events, and recommending what to do next. As a Full Stack Developer, you'll own features end to end, from the ingestion path that pulls telemetry off a BMS in a live facility, through the time-series layer that stores it, to the dashboard an operator is watching at 2am. This is a small team with real customers in production. Your code ships in days, not quarters, and it runs in facilities where being wrong has physical consequences. You'll work directly with the Principal Software & Architecture Lead, Product, and Solution Engineering. We move fast, avoid bureaucracy, and expect engineers to own outcomes rather than tickets. This is a hybrid role based in our Santa Clara office, and visa sponsorship is available. **Who We Are Looking For** You're a full-stack engineer who is comfortable on both sides of the line, and who gets interested rather than annoyed when the data is messy, the vendor's API is undocumented, and the protocol spec is a PDF from 2009. You likely: - Build front to back. You can trace a value from a Modbus register to a rendered chart without handing off, and you know where it's likely to break. - Take databases seriously. You know that a query plan, an index, and a migration on a large table are engineering decisions, not configuration. - Have worked with real time-series data at a volume where naive approaches stop working, and understand what that costs at read time and write time. - Debug production calmly. When CPU is pinned and a queue is backing up, you reason from evidence rather than restarting things. - Use AI tooling well. You get real leverage from Cursor, Claude Code, or similar, and your standards didn't drop when you started using it. **What You'll Do** **Product and front end** - Build operator-facing features for Neuron™ in React and TypeScript: real-time dashboards, alerting, alarm and ticket workflows, capacity planning views, and power-flow visualizations. - Build the interfaces the AI teammate works through: interaction panels, recommendation displays, approval workflows, and audit trails. - Keep large, data-dense views fast and responsive across devices. **Data ingestion and integrations** - Build and maintain the ingestion path that brings telemetry from customer sites into Neuron™: edge collectors, MQTT over AWS IoT Core, queue-based workers, and normalization into a canonical metric model. - Write integration modules against real building and power systems: Siemens Desigo, Schneider PME and EcoStruxure, Niagara, Eaton, and generic BACnet, Modbus, and SNMP sources. - Own the correctness of what lands: point mapping, unit and phase semantics, deduplication, and backfill. **Time-series platform** - Develop against PostgreSQL and TimescaleDB: hypertables, continuous aggregates, compression, and retention. - Design schema and migrations that stay safe as tables grow into the billions of rows. - Find and fix the performance problems that only appear with real customer data volumes. **Quality and operations** - Write tested, reviewed code, and contribute to CI/CD and automated testing. - Troubleshoot production issues across the stack, and share on-call as the platform scales. **Why Teserac** We're not building incremental improvements to legacy tools. We're re-architecting how data centers see, understand, and act on their own operations. - Ship features that directly shape how some of the world's most critical AI infrastructure is powered and managed. - Join a small engineering team where every developer has outsized impact and direct visibility into product decisions. - Work where AI, real-time systems, and physical infrastructure meet. - Grow with the company from Series A through scale. ## Requirements - **Required** - 7+ years building and shipping production software across the stack - Strong Python, ideally Django. Our backend is Django and Celery, and it's the language you'll write most days. - Strong PostgreSQL: schema design, query performance, and migrations you'd run against a live production database - Practical time-series experience. TimescaleDB is ideal, and deep experience with another time-series or high-volume streaming store transfers. - Solid React and TypeScript, and the judgment to keep a data-heavy interface fast - Experience with asynchronous and event-driven systems: task queues, pub/sub, streaming, or WebSockets - Comfortable on AWS. We run ECS Fargate, RDS, ElastiCache, and IoT Core. - Able to work independently, define your own scope from a rough requirement, and ship - **Preferred** - Industrial or IoT telemetry experience: BMS, EPMS, DCIM, SCADA, or similar OT data sources - Hands-on experience with industrial protocols: BACnet, Modbus, SNMP, or vendor BMS APIs - Data center infrastructure familiarity: power distribution topology, UPS and PDU behavior, or PUE - Experience building observability or monitoring products, commercial or internal - Early-stage startup experience, Seed through Series B - Nobody checks every box here. If some of these describe you, apply. ## Benefits - Base salary: $180,000–$230,000, plus stock options. - Health Care Plan (Medical, Dental & Vision) - Retirement Plan (401k, IRA) - Paid Time Off (Vacation, Sick & Public Holidays) - Family Leave (Maternity, Paternity) - Training & Development - Work From Home - Free Food & Snacks - Stock Option Plan - **How We Hire** - Our process usually includes a phone screen, a technical assessment, a conversation with the hiring manager, and an in-person interview loop in Santa Clara.