Top Tech Jobs & Startup Jobs in Seattle, WA

Owns end-to-end physical data center network implementation for hyperscale AI infrastructure, including fiber plant architecture, transceiver planning, structured cabling, optical link budgets, port-to-fiber mapping, and DCIM integration. Collaborates with construction, power, cooling, and design teams; develops technical specifications, SOPs, and basis-of-design documents; and plans cabling and optics across multiple hardware generations.

Build and manage a global spare-parts sourcing program for critical data center equipment. Responsibilities include qualifying and dual-sourcing suppliers, negotiating pricing and inventory agreements, setting stocking levels and reorder points, forecasting demand using failure data and maintenance schedules, and maintaining accurate parts and supplier records across sites and regional depots.

Build and operate production data pipelines integrating ERP/ATS/project management/telemetry into a queryable layer. Own the data model for a live knowledge graph. Ship SLA-backed datasets/services for tools and ML. Convert unstructured vendor/field data (PDFs, spreadsheets) into trusted structured inputs. Ensure data quality via tests, monitoring, and lineage, and use modern data stacks and LLM tools responsibly.

Own the contractor and extended workforce program from intake through offboarding. Manage staffing vendors, maintain compliant worker classification and onboarding processes, advise hiring managers on workforce solutions, improve vendor management systems and workflows, and partner with Legal, Finance, and IT on escalations, controls, reporting, and data protection.

Build and own production software for facility energy control, including protocol and gateway services, messaging and state layers, data contracts, constraint execution, and observability. The role requires high-throughput messaging, time-series data modeling, resilient service design, device-to-database data integrity, and real-time operational systems experience. Bonus technologies include Go, NATS, Redis, industrial protocols, Kubernetes, ArgoCD, SCADA, EMS, and Grafana.

Build production AI-powered software for hiring, finance, capital planning, contract analysis, and operational workflows. Develop LLM features, MCP servers, and agentic systems; embed with finance, legal, recruiting, accounting, and operations teams; translate expert workflows into structured data and automated processes; and ship autonomous, user-friendly products rapidly.

Build AI-powered software automating hiring, finance, capital planning, contract analysis, and operational workflows. Develop production features using LLM APIs, MCP servers, and agentic frameworks; integrate enterprise systems; transform expert processes into structured data and generated work; and collaborate directly with finance, legal, recruiting, accounting, and delivery teams. The role emphasizes autonomy, rapid execution, product judgment, and forward deployment with business experts.

Design and build end-to-end software primitives for AI infrastructure: domain modeling of power/datacenters/chips, authorization, audit, orchestration, vendor data ingestion (KMZ/BIM/Revit), and agent integration to enable safe, auditable agent operators. Ship production-quality systems and work across ambiguity to turn unstructured data into durable, composable entities.

Own control architecture for rotating machinery and test rigs, including compressors, motor drives, expansion turbines, and thermofluid loops. Develop safety interlocks, fault handling, speed-based capacity control, and hardware-in-the-loop validation. Tune controls on live machines, investigate model-to-plant discrepancies, integrate production chillers with site BMS and plant systems, and document systems for operations teams.

Build software systems for large-scale AI compute operations, including fleet health monitoring, automated repair and RMA workflows, hardware qualification, facility asset management, and structured operational procedures. Develop production features using Go, Python, or TypeScript; integrate LLMs and agentic tools; support on-call operations; and work closely with production engineers and facility operators to improve reliability and deployment speed.