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EnlyftPosted 4 weeks ago

Principal Software Engineer - Backend

HybridKirkland, Washington, United States

Full TimeSenior LevelBachelors DegreeSmall

Job Summary

Design and deploy scalable, high-performance solutions across the stack while establishing architectural standards for reliability, security, and performance. Help build the AI-native platform by designing agentic workflows that plan, call tools, and run multi-step tasks in production. Stay close to customers to understand their real workflows and carry that context back into architecture and roadmap decisions. Lead and mentor engineers across disciplines, promoting best practices in coding, testing, and deployment. Partner with product managers and stakeholders to define requirements and deliver integrated solutions. Own the lifecycle of complex, multi-area projects, ensuring timely delivery, resolving hard technical issues, and managing technical debt. Document key architectural designs and decisions to enable faster team learning. This role requires 14+ years of experience and involves hybrid work (3 days in office).

Required Qualifications

  • Bachelor's degree in Computer Science or a related field
  • 14+ years of experience
  • 4+ years in a principal or architect-level role
  • Deep expertise designing and implementing scalable, distributed systems
  • Strong command of software design patterns and architectural best practices
  • Expertise in modern programming languages and frameworks (e.g., Python, Node.js, Java)
  • Strong knowledge of database systems (e.g., SQL, NoSQL)
  • Strong knowledge of RESTful APIs
  • Strong knowledge of microservices architecture
  • Hands-on experience building and shipping GenAI or AI-agent capabilities in production
  • Experience connecting models to tools, APIs, and search to run real multi-step workflows
  • Experience with retrieval and semantic search to ground models in real data
  • Good instincts for keeping AI output accurate and cost and latency in check
  • Fluency with cloud platforms (AWS, Azure, or GCP)
  • Experience with containers (Docker, Kubernetes)
  • Comfort with modern DevOps and CI/CD practices

Desired Qualifications

  • Experience with retrieval and semantic search to ground models in real data is a strong plus
  • Good instincts for keeping AI output accurate and cost and latency in check

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