Principal Software Engineer – Backend

• Design and deploy scalable, high-performance solutions across the stack (backend, frontend, and beyond), and establish the architectural standards for reliability, security, and performance the team builds against
• Help build our AI-native platform - designing agentic workflows that plan, call tools, and run multi-step tasks in production, not just as prototypes
• Stay close to customers - understand their real workflows, sit with their hardest problems, and carry that context back into the architecture and roadmap
• Lead and mentor engineers across disciplines, promoting best practices in coding, testing, and deployment
• Partner with product managers, engineers, and other stakeholders to define requirements and deliver integrated solutions that meet both business and technical needs
• Own the lifecycle of complex, multi-area projects - ensuring timely, high-quality delivery, resolving hard technical issues, and managing technical debt with the judgment to keep momentum
• Document key architectural designs and decisions, and share knowledge so the team can build, debug, and learn faster

• Bachelor's degree in Computer Science or a related field, with 14+ years of experience, including 4+ years in a principal or architect-level role
• Deep expertise designing and implementing scalable, distributed systems, with 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, No
  
  SQL), RESTful APIs, and microservices architecture
• Hands-on experience building and shipping GenAI or AI-agent capabilities in production - 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 is a strong plus, along with good instincts for keeping AI output accurate and cost and latency in check
• Fluency with cloud platforms (AWS, Azure, or GCP) and containers (Docker, Kubernetes), and comfort with modern Dev Ops and CI/CD practices

Demonstrates deep expertise in designing and implementing scalable, distributed systems, with a strong command of software design patterns and architectural best practices. Proficient in building AI-native platforms and managing complex projects while ensuring high-quality delivery and effective collaboration with cross-functional teams.

• Scalable Distributed Systems Design
• AI-Agent Capabilities Development
• Cloud Platforms (AWS, Azure, GCP)
• Modern Programming Languages (Python, Node.js, Java)
• Microservices Architecture

• Software Design Patterns
• Architectural Best Practices
• Database Systems (SQL, No
  
  SQL)
• RESTful APIs
• Dev Ops Practices
• CI/CD Practices
• Containerization (Docker, Kubernetes)
• Semantic Search
• Retrieval Systems
• Multi-Step Workflow Implementation

• Leadership
• Mentoring
• Collaboration
• Problem-Solving
• Customer Engagement

• AI-Native Platform
• Architect-Level Role
• Technical Debt Management
• Integrated Solutions
• High-Performance Solutions

• AWS
• Azure
• GCP
• Docker
• Kubernetes