Principal Software Engineer, AI Cloud

Decision Foundry•Seatle, WA

1d•Remote

About The Position

Welcome to Decision Foundry - Data Analytics Division! We are proud to introduce ourselves as a certified "Great Place to Work," where we prioritize creating an exceptional work environment. As a global company, we embrace a diverse culture, fostering inclusivity across all levels. Originating from a well-established 19-year web analytics company, we remain dedicated to our employee-centric approach. By valuing our team members, we aim to enhance engagement and drive collective success. We are a leading Data Analytics & Salesforce consulting firm delivering transformative digital solutions for businesses across industries. Our expert team partners with clients to unlock the full potential of the Salesforce ecosystem, with a specialized focus on data-driven marketing, automation, and AI-powered personalization. We are seeking a Principal Software Engineer for our client who will define the technical vision and lead the design and implementation of AI Cloud’s distributed systems. As a key member of the AI Cloud leadership team, you will partner with principal engineers across the company to architect scalable, reliable, and secure infrastructure that supports millions of developers and thousands of enterprises.

Requirements

10+ years of software engineering experience, including 3+ years in technical leadership roles (Staff or Principal level)
Proven experience designing and building highly scalable distributed systems in production environments
Deep understanding of cloud infrastructure (AWS, Azure, GCP, or OCI), including compute, networking, and storage primitives
Proficiency in Go, Rust, or Java
Expertise in Kubernetes, microservices, and service mesh architectures
Strong foundation in observability, CI/CD, and infrastructure-as-code (Terraform, Pulumi, or CloudFormation)
Experience operating high-availability (99.99%+) production systems
Exceptional communication skills and ability to influence across technical and business domains
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience

Nice To Haves

Experience designing multi-cloud or cross-cloud abstractions and orchestration layers
Knowledge of container lifecycle management, networking, and policy enforcement
Prior experience in developer infrastructure, PaaS, or hyperscale SaaS environments
Background contributing to open source or developer-focused platforms is a plus.

Responsibilities

Define and drive the long-term technical strategy for AI Cloud’s control and data plane services.
Architect highly available, multi-region systems capable of operating seamlessly across multiple cloud providers.
Design APIs and service abstractions that integrate Desktop, Hub, and enterprise cloud services.
Establish standards for reliability, scalability, and observability across the AI Cloud platform.
Lead cross-functional technical discussions and influence architectural decisions company-wide.
Design and implement distributed systems for workload orchestration, service discovery, and lifecycle management.
Build and operate control plane components that manage multi-tenant workloads and cloud networking.
Develop infrastructure that delivers predictable performance, intelligent scaling, and automated failover.
Ensure security, data integrity, and compliance across global infrastructure footprint.
Partner with platform and product teams to deliver developer-friendly APIs and cloud experiences.
Align technical direction with business objectives for cloud growth and developer platform unification.
Evaluate emerging technologies (e.g., service meshes, container orchestration, edge computing) and guide adoption.
Drive initiatives that reduce latency, optimize cost, and improve cross-cloud performance.
Define metrics and SLAs for AI Cloud’s reliability and scalability.
Mentor senior, staff and principal engineers, fostering technical excellence and growth across teams.
Lead design reviews and guide critical production system decisions.
Drive a culture of operational excellence, ownership, and innovation.
Collaborate with engineering and product leadership to align priorities and resource planning.
Take part in on-call rotation for your team; respond to incidents, debug production issues, and drive continuous improvement of system reliability.