Top Tech Jobs & Startup Jobs in Seattle, WA

Lead front-end implementation using React and Next.js, mentor a small team, translate architecture into plans, ensure test coverage and performance, coordinate CI/CD and deployments, and collaborate with product, UX, and backend teams.

Design, develop, and maintain scalable full-stack applications for intermediary clearing and custody platforms. Collaborate with product, architecture, and engineering teams to modernize applications, implement cloud migrations, build APIs, automate workflows, and improve CI/CD, observability, security, and deployment practices in an Agile environment.

Design, implement, and manage large-scale GCP infrastructure using IaC (Terraform), containerization (Kubernetes/Docker), monitoring, security, and DR. Mentor junior engineers, optimize performance and costs, and document practices.

Own product vision and roadmap for a cloud-native data platform on GCP. Translate business needs into epics and user stories, prioritize ETL/ELT, databases, streaming, and BI work, coordinate onshore/offshore teams, ensure data governance, quality, and analytics readiness, and drive adoption of Snowflake and DOMO-based analytics.

Design, develop, and secure blockchain solutions including smart contracts and DApps. Collaborate with teams to integrate, optimize performance, audit security, document projects, and provide technical support and training.

Develop and maintain web applications across the full stack using Java/Spring Boot backend and Angular frontend. Build microservices, design RESTful APIs, integrate frontend components, work with Kafka and AWS S3 as needed, and collaborate with cross-functional teams to troubleshoot and deliver solutions throughout the SDLC.

Lead modernization of the Salesforce ecosystem by optimizing development practices, reducing technical debt, improving performance and integrations, implementing best practices and governance (focus on Service Cloud), driving version control adoption, and providing technical leadership and training to create scalable, cost-effective solutions.

Lead design, development, and deployment of production-grade Generative AI applications (LLM-based chatbots, agents, RAG systems). Hands-on coding in Python, integrate and benchmark models, build ingestion and vector retrieval pipelines, design architecture for performance and cost, mentor engineers, and implement AI governance, safety, and monitoring.

Build and maintain scalable Python/FastAPI backend services, integrate generative AI and LLMs, implement RAG/vector DB semantic search, design agent-based workflows, develop APIs and microservices, enable async/event-driven processing, support cloud-native deployments (Docker/Kubernetes), and collaborate across frontend, DevOps, and product teams to deliver secure, observable AI-driven employee support platform.

Design, build, and scale production-ready generative AI systems: multi-agent workflows, advanced RAG pipelines, LLM integration and fine-tuning, scalable FastAPI backends, Dockerized deployments, monitoring, and GenAI optimization for latency, cost, and reliability.