Principal Software Engineer – Backend

enlyft

Kirkland (WA)

On-site

USD 180,000 - 260,000

Full time

14 days+

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Job summary

Jobtailor is seeking an experienced principal/architect-level engineer in Kirkland, WA to design and deploy scalable, high-performance systems across the stack. You will lead the AI-native platform, crafting agentic workflows that plan, call tools, and execute multi-step tasks in production, not just prototypes.

You will mentor engineers, collaborate with product and stakeholders, and drive complex projects end-to-end while managing technical debt and documenting architectural decisions.

Qualifications

14+ years of professional software engineering experience, including architecture.

Responsibilities

Design and deploy scalable, high-performance solutions across the stack and establish 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

Skills

Scalable distributed systems

AI-agent capabilities

Python

Node.js

Java

SQL

NoSQL

RESTful APIs

Microservices

GenAI workflows

Semantic search

CI/CD

Cloud platforms

AWS

Azure

GCP

Docker

Kubernetes

Education

Bachelor's degree in Computer Science

Tools

Docker

Kubernetes

AWS

Azure

GCP

Job description

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

Requirements

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, NoSQL), 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 DevOps and CI/CD practices

Core Competencies

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.

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