Join a technology-driven team building the next generation of AI-powered marketing infrastructure. In this role, you will strengthen and evolve the systems that support complex marketing operations, lead management, and data governance.
Responsibilities
Develop a unified lead intake platform that captures leads from websites, portals, webinars, events, partners, and imported lists, ensuring validation, deduplication, consent management, and enrichment.
Build AI-powered lead qualification and scoring capabilities using signals such as product usage, learning activity, website behavior, intent data, and company information.
Create intelligent lead routing systems that assign prospects based on territory, team capacity, availability, and priority, with transparent decision records.
Improve lead hand-offs by tracking each prospect from initial capture to first sales interaction, identifying delays, and ensuring timely follow-up.
Develop a self-service campaign management layer that allows Marketing Operations to configure routing, prioritization, and nurturing rules without creating additional workflows.
Requirements
Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline
Principal Member of Technical Staff (PMTS) Software Development Engineer to join AMD Silo AI and drive the technical development of the AMD Inference Microservice (AIM) ecosystem in northern America.
Responsibilities
Own and drive design of complex, data-heavy backend services and user-facing applications for AI/GPU and platform workflows (Kubernetes, APIs, integrations)
Set and evolve architectural direction for Kubernetes toolchain, APIs and UIs enabling core AI workflows; ensure security, scalability, and maintainability under real customer load
Optimize systems for efficiency, performance and reliability; debug and resolve cross-cutting production issues
Embed engineering excellence: code quality, automated testing, CI/CD, observability, and API/design standards across the teams you work with
Influence AIM ecosystem roadmap through deep understanding of customer needs, market direction, and technical feasibility; translating requirements into prioritized engineering work
Requirements
Bachelor’s in Computer Science
Master’s in Computer Science
Nice to have: GPU workloads
Nice to have: ML/LLM training or inference pipelines
As a Staff Backend Engineer, you'll be hands-on and writing production code, working closely with the Foundations lead. You'll stay on one team but spend a lot of your time alongside other teams, helping them adopt a new pattern, writing code with them and making sure it works for their part of the product. This isn't a feature team role, and it isn't DevOps or SRE either. It's backend engineering whose impact shows up across the whole of Quo.
Locations (2)
United States
Canada
Compensation
The annual base salary range for this position is as follows, plus equity and benefits:
- SF Bay Area, Los Angeles, Seattle, Portland, Boston, New York, and Washington, DC Metro: $205,000 - $242,000 USD
- All other US Locations: $186,000 - $217,000 USD
- Canada: $189,000 - $222,000 CAD
Responsibilities
Lead the technical work on our REST to GraphQL migration, building the core pieces yourself and the patterns that let every other team finish theirs.
Shape how our GraphQL architecture grows, including breaking one large graph into supergraphs and subgraphs that teams can own and change independently.
Help rework authentication and authorization across Quo, working directly with each team it touches and writing code alongside them.
A hands-on technical leadership role within the Behavioural team focused on building intelligence layers that turn customer signals into marketing triggers.
Compensation
The base pay range for this position is $147,300 - $192,000 CAD/year, which can include additional bonus depending on the position ultimately offered, in addition to a full range of medical, financial, and/or benefits. The base pay offered may vary depending on job-related knowledge, skills, and experience.
Responsibilities
Shape the Behavioral Platform Architecture: Help define the technical vision, system boundaries, and architecture for services that transform customer activity signals into actionable trigger events.
Lead by Example: Be a hands-on technical leader who contributes directly to high-impact work through design, implementation, code review, debugging, and production support.
Build the Behavioral Decisioning Engine: Design and implement services that detect behavioral patterns across events, correlate signals across time windows, and determine trigger eligibility.
Design Stateful Contact Context: Help architect systems that maintain the short-lived behavioral state and lookback windows needed to evaluate patterns like ‘action without completion,’ multi-event intent signals, and state-change-driven triggers.
Establish a Reusable Pattern Framework: Help build declarative or rule-based capabilities that allow new behavioral triggers to be defined, configured, evaluated, and extended efficiently over time.
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