Top Tech Jobs & Startup Jobs

Work at the intersection of engineering and customers to deploy AI use cases in construction environments. Design AI workflows for CAD drawings, specifications, contracts, and schedules; integrate and configure the platform; write code and prototype bespoke solutions; translate customer issues into technical requirements; and validate AI outputs against construction standards.

Lead frontend architecture and implement scalable B2B features using React and TypeScript. Design domain boundaries, build reusable components, ensure type-safe code, tests, performance optimization, and collaborate with backend and cross-functional teams to integrate APIs and AI features.

Lead MLOps Engineer responsible for building and automating the lifecycle of multimodal agentic AI: orchestration (LangChain/LangGraph), training pipelines for LLMs and CV, containerized model deployment, low-latency inference, model monitoring/drift detection, and optimizing ML infrastructure for performance and cost.

Design and build scalable, high-performance backend services in Go that process large-scale structured and unstructured data, orchestrate AI workflows, expose reliable APIs, ensure reliability and observability, optimize performance, deploy on AWS with Docker/Kubernetes, and collaborate with frontend, ML, and platform teams while mentoring juniors.

Lead quality, performance, and reliability strategy for an agentic AI SaaS platform. Architect automated testing, SLIs/SLOs, CI/CD quality gates, verify integrations with legacy AEC systems, and build a Quality Engineering team to ensure enterprise-grade uptime, latency, and throughput.

Architect, deploy, and operate production-grade Kubernetes clusters and multi-region AWS infrastructure with Terraform. Build GitLab CI/CD pipelines to deploy containerized microservices via Helm/Docker, implement monitoring and autoscaling for bursty AI workloads, and ensure enterprise-grade security and compliance.

Design and deliver end-to-end computer vision and multi-agent AI architectures for AEC use cases. Lead R&D, convert SOTA research into production-ready, latency- and cost-optimized models, build multi-modal knowledge graphs to ground agents, and implement feedback loops using production telemetry to improve performance.

Design and implement an end-to-end TypeScript/Cypress test automation framework to validate non-deterministic, agentic AI outputs in AEC workflows, audit complex user journeys, ensure integrations, and automate regression and scaling tests while collaborating with Product and Engineering.

Design, implement, and maintain high-performance, distributed backend services in Go. Build scalable APIs, process large multi-tenant datasets, ensure reliability via testing and observability, optimize performance, deploy on AWS using Docker/Kubernetes, and collaborate with frontend, ML, and platform teams.

Lead development of the spatial reasoning engine for an agentic AI platform: build 3D semantic reconstruction, geometric deep learning pipelines, multi-modal fusion into spatio-temporal knowledge graphs, design agentic inference and affordance mapping, and optimize models for production at scale.